Point cloud data transmission device, point cloud data transmission method, point cloud data reception device, and point cloud data reception method

ABSTRACT

Disclosed herein is a method of transmitting point cloud data, including encoding geometry data of point cloud data, encoding attribute data of the point cloud data based on the geometry data, and transmitting the encoded geometry data, the encoded attribute data, and signaling data.

CROSS-REFERENCE TO RELATED APPLICATIONS

This application is a continuation of U.S. application Ser. No.17/520,342, filed on Nov. 5, 2021, which claims the benefit of earlierfiling date and right of priority to Korean Patent Application No.10-2020-0146596, filed on Nov. 5, 2020, the contents of which are herebyincorporated by reference herein in their entirety.

TECHNICAL FIELD

Embodiments relate to a method and apparatus for processing point cloudcontent.

BACKGROUND

Point cloud content is content represented by a point cloud, which is aset of points belonging to a coordinate system representing athree-dimensional space (or volume). The point cloud content may expressmedia configured in three dimensions, and is used to provide variousservices such as virtual reality (VR), augmented reality (AR), mixedreality (MR), XR (Extended Reality), and self-driving services. However,tens of thousands to hundreds of thousands of point data are required torepresent point cloud content. Therefore, there is a need for a methodfor efficiently processing a large amount of point data.

In other words, a high throughput is required to transmit and receivedata of the point cloud. Accordingly, in the process of transmitting andreceiving the point cloud data, in which encoding for compression anddecoding for decompression are performed, the computational operation iscomplicated and time-consuming due to the large volume of the pointcloud data.

SUMMARY

An object of the present disclosure devised to solve the above-describedproblems is to provide a point cloud data transmission device, a pointcloud data transmission method, a point cloud data reception device, anda point cloud data reception method for efficiently transmitting andreceiving a point cloud

Another object of the present disclosure is to provide a point clouddata transmission device, a point cloud data transmission method, apoint cloud data reception device, and a point cloud data receptionmethod for addressing latency and encoding/decoding complexity.

Another object of the present disclosure is to provide a point clouddata transmission point cloud data device, a transmission method, apoint cloud data reception device, and a point cloud data receptionmethod that may allow the reception device to efficiently perform buffermanagement when entropy continuity is given between multiple slices.

Objects of the present disclosure are not limited to the aforementionedobjects, and other objects of the present disclosure which are notmentioned above will become apparent to those having ordinary skill inthe art upon examination of the following description.

To achieve these objects and other advantages and in accordance with thepurpose of the disclosure, as embodied and broadly described herein, amethod of transmitting point cloud data may include encoding geometrydata of the point cloud data, encoding attribute data of the point clouddata based on the geometry data, and transmitting the encoded geometrydata, the encoded attribute data, and signaling data.

According to embodiments, the encoded geometry data is segmented into aplurality of slices and a context of one of the plurality of slices isreferenced by at least one other slice.

According to embodiments, the signaling data includes slice relatedinformation and buffer control related information.

According to embodiments, the buffer control related informationincludes at least information for indicating whether a context of acurrent slice is referenced by at least one other slice, or informationfor identifying the number of times the context of the current slice isreferenced when the context of the current slice is referenced by the atleast one other slice.

According to embodiments, an apparatus for transmitting point cloud datamay include a geometry encoder configured to encode geometry data of thepoint cloud data, an attribute encoder configured to encode attributedata of the point cloud data based on the geometry data, and atransmitter configured to transmit the encoded geometry data, theencoded attribute data, and signaling data.

According to embodiments, the encoded geometry data is segmented into aplurality of slices and a context of one of the plurality of slices isreferenced by at least one other slice.

According to embodiments, the signaling data includes slice relatedinformation and buffer control related information.

According to embodiments, the buffer control related informationincludes at least information for indicating whether a context of acurrent slice is referenced by at least one other slice, or informationfor identifying the number of times the context of the current slice isreferenced when the context of the current slice is referenced by the atleast one other slice.

According to embodiments, a method of receiving point cloud data mayinclude receiving geometry data, attribute data, and signaling data,decoding the geometry data based on the signaling data, decoding theattribute data based on the signaling data and the decoded geometrydata, and rendering the decoded point cloud data based on the signalingdata.

According to embodiments, the geometry data is included in a pluralityof slices and a context of one of the plurality of slices is referencedby at least one other slice.

According to embodiments, the signaling data includes slice relatedinformation and buffer control related information.

According to embodiments, the buffer control related informationincludes at least information for indicating whether a context of acurrent slice is referenced by at least one other slice, or informationfor identifying the number of times the context of the current slice isreferenced when the context of the current slice is referenced by the atleast one other slice.

According to embodiments, the decoding of the geometry data comprisescontrolling buffer storage of a context of a current slice based on thesignaling related information and the buffer control relatedinformation.

According to embodiments, the decoding of the geometry data comprises,when it is determined that the context of the current slice is notreferenced by the at least one other slice based on the signalingrelated information and the buffer control related information, deletingthe context of the current slice from a buffer.

According to embodiments, the decoding of the geometry data comprises,when it is determined that the context of the current slice isreferenced by the at least one other slice based on the signalingrelated information and the buffer control related information, deletingthe context of the current slice from a buffer after the current slicecontext is referenced by the at least one other slice.

BRIEF DESCRIPTION OF THE DRAWINGS

The accompanying drawings, which are included to provide a furtherunderstanding of the disclosure and are incorporated in and constitute apart of this application, illustrate embodiment(s) of the disclosure andtogether with the description serve to explain the principle of thedisclosure.

FIG. 1 illustrates an exemplary point cloud content providing systemaccording to embodiments.

FIG. 2 is a block diagram illustrating a point cloud content providingoperation according to embodiments.

FIG. 3 illustrates an exemplary process of capturing a point cloud videoaccording to embodiments.

FIG. 4 illustrates an exemplary block diagram of point cloud videoencoder according to embodiments.

FIG. 5 illustrates an example of voxels in a 3D space according toembodiments.

FIG. 6 illustrates an example of octree and occupancy code according toembodiments.

FIG. 7 illustrates an example of a neighbor node pattern according toembodiments.

FIG. 8 illustrates an example of point configuration of a point cloudcontent for each LOD according to embodiments.

FIG. 9 illustrates an example of point configuration of a point cloudcontent for each LOD according to embodiments.

FIG. 10 illustrates an example of a block diagram of a point cloud videodecoder according to embodiments.

FIG. 11 illustrates an example of a point cloud video decoder accordingto embodiments.

FIG. 12 illustrates a configuration for point cloud video encoding of atransmission device according to embodiments.

FIG. 13 illustrates a configuration for point cloud video decoding of areception device according to embodiments.

FIG. 14 illustrates an exemplary structure operatively connectable witha method/device for transmitting and receiving point cloud dataaccording to embodiments.

FIGS. 15 and 16 illustrate encoding, transmission, and decoding of pointcloud data according to embodiments.

FIG. 17 illustrates an example of configuring one or more bricks in atree structure according to embodiments.

FIGS. 18A to 18C illustrate examples of a matching relationship betweentree layers and slices established to transmit point cloud databelonging to a brick according to embodiments.

FIG. 19 is a diagram illustrating an example of layer-basedconfiguration of point cloud data according to embodiments.

FIG. 20 is a diagram illustrating an example in which a geometrybitstream and an attribute bitstream are included in respective slicesaccording to embodiments.

FIG. 21(a) is a diagram illustrating an example of dividing a geometrybitstream into multiple slices according to embodiments.

FIG. 21(b) is a diagram illustrating an example of dividing an attributebitstream into multiple slices according to embodiments.

FIG. 22(a) is a diagram illustrating another example of dividing ageometry bitstream into multiple slices according to embodiments.

FIG. 22(b) is a diagram illustrating another example of dividing anattribute bitstream into multiple slices according to embodiments.

FIG. 23 illustrates an exemplary method of sorting a geometry bitstreamand an attribute bitstream according to embodiments.

FIG. 24 illustrates another exemplary method of sorting a geometrybitstream and an attribute bitstream according to embodiments.

FIG. 25A is a diagram illustrating an example of dependency betweenslices in a bitstream structure according to embodiments.

FIG. 25B is a diagram illustrating an example of contexts generated inrespective slices when inter-slice dependency occurs according toembodiments.

FIGS. 25C to 25E are diagrams illustrating examples of context buffercontrol when inter-slice dependency occurs according to embodiments.

FIGS. 26A to 26D are diagrams illustrating examples of a neighborstructure according to embodiments.

FIG. 27 is a diagram illustrating an example of a bitstream structure ofpoint cloud data for transmission/reception according to embodiments.

FIG. 28 shows an embodiment of a syntax structure of a sequenceparameter set according to embodiments.

FIG. 29 shows an embodiment of a syntax structure of a sequenceparameter set according to embodiments.

FIG. 30 shows an exemplary syntax structure of a geometry parameter setaccording to embodiments.

FIG. 31 shows another exemplary syntax structure of a geometry parameterset according to embodiments.

FIG. 32 shows an exemplary syntax structure of an attribute parameterset according to embodiments.

FIG. 33 shows an exemplary syntax structure of an attribute parameterset according to embodiments.

FIG. 34 shows an exemplary syntax structure of geometry_slice_bitstream() according to embodiments.

FIG. 35 shows an exemplary syntax structure of a geometry slice headeraccording to embodiments.

FIG. 36 shows an exemplary syntax structure of a geometry data unitheader according to embodiments.

FIG. 37 shows an exemplary syntax structure of a geometry data unitaccording to embodiments.

FIG. 38 shows an exemplary syntax structure ofattribute_slice_bitstream( ) according to embodiments.

FIG. 39 shows an exemplary syntax structure of an attribute slice headeraccording to embodiments.

FIG. 40 shows another exemplary syntax structure of an attribute dataunit header according to embodiments.

FIG. 41 shows another exemplary syntax structure of an attribute dataunit according to embodiments.

FIG. 42 illustrates another example of a point cloud transmission deviceaccording to embodiments.

FIG. 43 is a block diagram illustrating another example of a point cloudreception device according to embodiments.

DETAILED DESCRIPTION

Description will now be given in detail according to exemplaryembodiments disclosed herein, with reference to the accompanyingdrawings. For the sake of brief description with reference to thedrawings, the same or equivalent components may be provided with thesame reference numbers, and description thereof will not be repeated. Itshould be noted that the following examples are only for embodying thepresent disclosure and do not limit the scope of the present disclosure.What can be easily inferred by an expert in the technical field to whichthe present invention belongs from the detailed description and examplesof the present disclosure is to be interpreted as being within the scopeof the present disclosure.

The detailed description in this present specification should beconstrued in all aspects as illustrative and not restrictive. The scopeof the disclosure should be determined by the appended claims and theirlegal equivalents, and all changes coming within the meaning andequivalency range of the appended claims are intended to be embracedtherein.

Reference will now be made in detail to the preferred embodiments of thepresent disclosure, examples of which are illustrated in theaccompanying drawings. The detailed description, which will be givenbelow with reference to the accompanying drawings, is intended toexplain exemplary embodiments of the present disclosure, rather than toshow the only embodiments that can be implemented according to thepresent disclosure. The following detailed description includes specificdetails in order to provide a thorough understanding of the presentdisclosure. However, it will be apparent to those skilled in the artthat the present disclosure may be practiced without such specificdetails. Although most terms used in this specification have beenselected from general ones widely used in the art, some terms have beenarbitrarily selected by the applicant and their meanings are explainedin detail in the following description as needed. Thus, the presentdisclosure should be understood based upon the intended meanings of theterms rather than their simple names or meanings. In addition, thefollowing drawings and detailed description should not be construed asbeing limited to the specifically described embodiments, but should beconstrued as including equivalents or substitutes of the embodimentsdescribed in the drawings and detailed description.

FIG. 1 shows an exemplary point cloud content providing system accordingto embodiments.

The point cloud content providing system illustrated in FIG. 1 mayinclude a transmission device 10000 and a reception device 10004. Thetransmission device 10000 and the reception device 10004 are capable ofwired or wireless communication to transmit and receive point clouddata.

The point cloud data transmission device 10000 according to theembodiments may secure and process point cloud video (or point cloudcontent) and transmit the same. According to embodiments, thetransmission device 10000 may include a fixed station, a basetransceiver system (BTS), a network, an artificial intelligence (AI)device and/or system, a robot, an AR/VR/XR device and/or server.According to embodiments, the transmission device 10000 may include adevice, a robot, a vehicle, an AR/VR/XR device, a portable device, ahome appliance, an Internet of Thing (IoT) device, and an AIdevice/server which are configured to perform communication with a basestation and/or other wireless devices using a radio access technology(e.g., 5G New RAT (NR), Long Term Evolution (LTE)).

The transmission device 10000 according to the embodiments includes apoint cloud video acquisition unit 10001, a point cloud video encoder10002, and/or a transmitter (or communication module) 10003.

The point cloud video acquisition unit 10001 according to theembodiments acquires a point cloud video through a processing processsuch as capture, synthesis, or generation. The point cloud video ispoint cloud content represented by a point cloud, which is a set ofpoints positioned in a 3D space, and may be referred to as point cloudvideo data. The point cloud video according to the embodiments mayinclude one or more frames. One frame represents a still image/picture.Therefore, the point cloud video may include a point cloudimage/frame/picture, and may be referred to as a point cloud image,frame, or picture.

The point cloud video encoder 10002 according to the embodiments encodesthe acquired point cloud video data. The point cloud video encoder 10002may encode the point cloud video data based on point cloud compressioncoding. The point cloud compression coding according to the embodimentsmay include geometry-based point cloud compression (G-PCC) coding and/orvideo-based point cloud compression (V-PCC) coding or next-generationcoding. The point cloud compression coding according to the embodimentsis not limited to the above-described embodiment. The point cloud videoencoder 10002 may output a bitstream containing the encoded point cloudvideo data. The bitstream may contain not only the encoded point cloudvideo data, but also signaling information related to encoding of thepoint cloud video data.

The transmitter 10003 according to the embodiments transmits thebitstream containing the encoded point cloud video data. The bitstreamaccording to the embodiments is encapsulated in a file or segment (forexample, a streaming segment), and is transmitted over various networkssuch as a broadcasting network and/or a broadband network. Although notshown in the figure, the transmission device 10000 may include anencapsulator (or an encapsulation module) configured to perform anencapsulation operation. According to embodiments, the encapsulator maybe included in the transmitter 10003. According to embodiments, the fileor segment may be transmitted to the reception device 10004 over anetwork, or stored in a digital storage medium (e.g., USB, SD, CD, DVD,Blu-ray, HDD, SSD, etc.). The transmitter 10003 according to theembodiments is capable of wired/wireless communication with thereception device 10004 (or the receiver 10005) over a network of 4G, 5G,6G, etc. In addition, the transmitter may perform a necessary dataprocessing operation according to the network system (e.g., a 4G, 5G or6G communication network system). The transmission device 10000 maytransmit the encapsulated data in an on-demand manner.

The reception device 10004 according to the embodiments includes areceiver 10005, a point cloud video decoder 10006, and/or a renderer10007. According to embodiments, the reception device 10004 may includea device, a robot, a vehicle, an AR/VR/XR device, a portable device, ahome appliance, an Internet of Things (IoT) device, and an AIdevice/server which are configured to perform communication with a basestation and/or other wireless devices using a radio access technology(e.g., 5G New RAT (NR), Long Term Evolution (LTE)).

The receiver 10005 according to the embodiments receives the bitstreamcontaining the point cloud video data or the file/segment in which thebitstream is encapsulated from the network or storage medium. Thereceiver 10005 may perform necessary data processing according to thenetwork system (for example, a communication network system of 4G, 5G,6G, etc.). The receiver 10005 according to the embodiments maydecapsulate the received file/segment and output a bitstream. Accordingto embodiments, the receiver 10005 may include a decapsulator (or adecapsulation module) configured to perform a decapsulation operation.The decapsulator may be implemented as an element (or component ormodule) separate from the receiver 10005.

The point cloud video decoder 10006 decodes the bitstream containing thepoint cloud video data. The point cloud video decoder 10006 may decodethe point cloud video data according to the method by which the pointcloud video data is encoded (for example, in a reverse process of theoperation of the point cloud video encoder 10002). Accordingly, thepoint cloud video decoder 10006 may decode the point cloud video data byperforming point cloud decompression coding, which is the inverseprocess of the point cloud compression. The point cloud decompressioncoding includes G-PCC coding.

The renderer 10007 renders the decoded point cloud video data. Accordingto an embodiment, the render may render the decoded point cloud videodata according to a viewport, etc. The renderer 10007 may output pointcloud content by rendering not only the point cloud video data but alsoaudio data. According to embodiments, the renderer 10007 may include adisplay configured to display the point cloud content. According toembodiments, the display may be implemented as a separate device orcomponent rather than being included in the renderer 10007.

The arrows indicated by dotted lines in the drawing represent atransmission path of feedback information acquired by the receptiondevice 10004. The feedback information is information for reflectinginteractivity with a user who consumes the point cloud content, andincludes information about the user (e.g., head orientation information,viewport information, and the like). In particular, when the point cloudcontent is content for a service (e.g., self-driving service, etc.) thatrequires interaction with the user, the feedback information may beprovided to the content transmitting side (e.g., the transmission device10000) and/or the service provider. According to embodiments, thefeedback information may be used in the reception device 10004 as wellas the transmission device 10000, or may not be provided.

The head orientation information according to the embodiments mayrepresent information about a position, orientation, angle, and motionof a user's head. The reception device 10004 according to theembodiments may calculate viewport information based on the headorientation information. The viewport information is information about aregion of a point cloud video that the user is viewing (that is, aregion that the user is currently viewing). That is, the viewportinformation is information about a region that the user is currentlyviewing in the point cloud video. In other words, the viewport orviewport region may represent a region that the user is viewing in thepoint cloud video. A viewpoint is a point that the user is viewing inthe point cloud video, and may represent a center point of the viewportregion. That is, the viewport is a region centered on a viewpoint, andthe size and shape of the region may be determined by a field of view(FOV). Accordingly, the reception device 10004 may extract the viewportinformation based on a vertical or horizontal FOV supported by thedevice as well as the head orientation information. In addition, thereception device 10004 may perform gaze analysis or the like based onthe head orientation information and/or the viewport information todetermine the way the user consumes a point cloud video, a region thatthe user gazes at in the point cloud video, and the gaze time. Accordingto embodiments, the reception device 10004 may transmit feedbackinformation including the result of the gaze analysis to thetransmission device 10000. According to embodiments, a device such as aVR/XR/AR/MR display may extract a viewport region based on theposition/orientation of a user's head and a vertical or horizontal FOVsupported by the device. According to embodiments, the head orientationinformation and the viewport information may be referred to as feedbackinformation, signaling information, or metadata.

The feedback information according to the embodiments may be acquired inthe rendering and/or display process. The feedback information may besecured by one or more sensors included in the reception device 10004.According to embodiments, the feedback information may be secured by therenderer 10007 or a separate external element (or device, component, orthe like). The dotted lines in FIG. 1 represent a process oftransmitting the feedback information secured by the renderer 10007. Thefeedback information may not only be transmitted to the transmittingside, but also be consumed by the receiving side. That is, the pointcloud content providing system may process (encode/decode/render) pointcloud data based on the feedback information. For example, the pointcloud video decoder 10006 and the renderer 10007 may preferentiallydecode and render only the point cloud video for a region currentlyviewed by the user, based on the feedback information, that is, the headorientation information and/or the viewport information.

The reception device 10004 may transmit the feedback information to thetransmission device 10000. The transmission device 10000 (or the pointcloud video encoder 10002) may perform an encoding operation based onthe feedback information. Accordingly, the point cloud content providingsystem may efficiently process necessary data (e.g., point cloud datacorresponding to the user's head position) based on the feedbackinformation rather than processing (encoding/decoding) the entire pointcloud data, and provide point cloud content to the user.

According to embodiments, the transmission device 10000 may be called anencoder, a transmitting device, a transmitter, a transmission system, orthe like, and the reception device 10004 may be called a decoder, areceiving device, a receiver, a reception system, or the like.

The point cloud data processed in the point cloud content providingsystem of FIG. 1 according to embodiments (through a series of processesof acquisition/encoding/transmission/decoding/rendering) may be referredto as point cloud content data or point cloud video data. According toembodiments, the point cloud content data may be used as a conceptcovering metadata or signaling information related to the point clouddata.

The elements of the point cloud content providing system illustrated inFIG. 1 may be implemented by hardware, software, a processor, and/or acombination thereof.

FIG. 2 is a block diagram illustrating a point cloud content providingoperation according to embodiments.

The block diagram of FIG. 2 shows the operation of the point cloudcontent providing system described in FIG. 1 . As described above, thepoint cloud content providing system may process point cloud data basedon point cloud compression coding (e.g., G-PCC).

The point cloud content providing system according to the embodiments(for example, the point cloud transmission device 10000 or the pointcloud video acquisition unit 10001) may acquire a point cloud video(20000). The point cloud video is represented by a point cloud belongingto a coordinate system for expressing a 3D space. The point cloud videoaccording to the embodiments may include a Ply (Polygon File format orthe Stanford Triangle format) file. When the point cloud video has oneor more frames, the acquired point cloud video may include one or morePly files. The Ply files contain point cloud data, such as pointgeometry and/or attributes. The geometry includes positions of points.The position of each point may be represented by parameters (forexample, values of the X, Y, and Z axes) representing athree-dimensional coordinate system (e.g., a coordinate system composedof X, Y and Z axes). The attributes include attributes of points (e.g.,information about texture, color (in YCbCr or RGB), reflectance r,transparency, etc. of each point). A point has one or more attributes.For example, a point may have an attribute that is a color, or twoattributes that are color and reflectance. According to embodiments, thegeometry may be called positions, geometry information, geometry data,or the like, and the attribute may be called attributes, attributeinformation, attribute data, or the like. The point cloud contentproviding system (for example, the point cloud transmission device 10000or the point cloud video acquisition unit 10001) may secure point clouddata from information (e.g., depth information, color information, etc.)related to the acquisition process of the point cloud video.

The point cloud content providing system (for example, the transmissiondevice 10000 or the point cloud video encoder 10002) according to theembodiments may encode the point cloud data (20001). The point cloudcontent providing system may encode the point cloud data based on pointcloud compression coding. As described above, the point cloud data mayinclude the geometry and attributes of a point. Accordingly, the pointcloud content providing system may perform geometry encoding of encodingthe geometry and output a geometry bitstream. The point cloud contentproviding system may perform attribute encoding of encoding attributesand output an attribute bitstream. According to embodiments, the pointcloud content providing system may perform the attribute encoding basedon the geometry encoding. The geometry bitstream and the attributebitstream according to the embodiments may be multiplexed and output asone bitstream. The bitstream according to the embodiments may furthercontain signaling information related to the geometry encoding andattribute encoding.

The point cloud content providing system (for example, the transmissiondevice 10000 or the transmitter 10003) according to the embodiments maytransmit the encoded point cloud data (20002). As illustrated in FIG. 1, the encoded point cloud data may be represented by a geometrybitstream and an attribute bitstream. In addition, the encoded pointcloud data may be transmitted in the form of a bitstream together withsignaling information related to encoding of the point cloud data (forexample, signaling information related to the geometry encoding and theattribute encoding). The point cloud content providing system mayencapsulate a bitstream that carries the encoded point cloud data andtransmit the same in the form of a file or segment.

The point cloud content providing system (for example, the receptiondevice 10004 or the receiver 10005) according to the embodiments mayreceive the bitstream containing the encoded point cloud data. Inaddition, the point cloud content providing system (for example, thereception device 10004 or the receiver 10005) may demultiplex thebitstream.

The point cloud content providing system (e.g., the reception device10004 or the point cloud video decoder 10005) may decode the encodedpoint cloud data (e.g., the geometry bitstream, the attribute bitstream)transmitted in the bitstream. The point cloud content providing system(for example, the reception device 10004 or the point cloud videodecoder 10005) may decode the point cloud video data based on thesignaling information related to encoding of the point cloud video datacontained in the bitstream. The point cloud content providing system(for example, the reception device 10004 or the point cloud videodecoder 10005) may decode the geometry bitstream to reconstruct thepositions (geometry) of points. The point cloud content providing systemmay reconstruct the attributes of the points by decoding the attributebitstream based on the reconstructed geometry. The point cloud contentproviding system (for example, the reception device 10004 or the pointcloud video decoder 10005) may reconstruct the point cloud video basedon the positions according to the reconstructed geometry and the decodedattributes.

The point cloud content providing system according to the embodiments(for example, the reception device 10004 or the renderer 10007) mayrender the decoded point cloud data (20004). The point cloud contentproviding system (for example, the reception device 10004 or therenderer 10007) may render the geometry and attributes decoded throughthe decoding process, using various rendering methods. Points in thepoint cloud content may be rendered to a vertex having a certainthickness, a cube having a specific minimum size centered on thecorresponding vertex position, or a circle centered on the correspondingvertex position. All or part of the rendered point cloud content isprovided to the user through a display (e.g., a VR/AR display, a generaldisplay, etc.).

The point cloud content providing system (for example, the receptiondevice 10004) according to the embodiments may secure feedbackinformation (20005). The point cloud content providing system may encodeand/or decode point cloud data based on the feedback information. Thefeedback information and the operation of the point cloud contentproviding system according to the embodiments are the same as thefeedback information and the operation described with reference to FIG.1 , and thus detailed description thereof is omitted.

FIG. 3 illustrates an exemplary process of capturing a point cloud videoaccording to embodiments.

FIG. 3 illustrates an exemplary point cloud video capture process of thepoint cloud content providing system described with reference to FIGS. 1to 2 .

Point cloud content includes a point cloud video (images and/or videos)representing an object and/or environment located in various 3D spaces(e.g., a 3D space representing a real environment, a 3D spacerepresenting a virtual environment, etc.). Accordingly, the point cloudcontent providing system according to the embodiments may capture apoint cloud video using one or more cameras (e.g., an infrared cameracapable of securing depth information, an RGB camera capable ofextracting color information corresponding to the depth information,etc.), a projector (e.g., an infrared pattern projector to secure depthinformation), a LiDAR, or the like. The point cloud content providingsystem according to the embodiments may extract the shape of geometrycomposed of points in a 3D space from the depth information and extractthe attributes of each point from the color information to secure pointcloud data. An image and/or video according to the embodiments may becaptured based on at least one of the inward-facing technique and theoutward-facing technique.

The left part of FIG. 3 illustrates the inward-facing technique. Theinward-facing technique refers to a technique of capturing images acentral object with one or more cameras (or camera sensors) positionedaround the central object. The inward-facing technique may be used togenerate point cloud content providing a 360-degree image of a keyobject to the user (e.g., VR/AR content providing a 360-degree image ofan object (e.g., a key object such as a character, player, object, oractor) to the user).

The right part of FIG. 3 illustrates the outward-facing technique. Theoutward-facing technique refers to a technique of capturing images anenvironment of a central object rather than the central object with oneor more cameras (or camera sensors) positioned around the centralobject. The outward-facing technique may be used to generate point cloudcontent for providing a surrounding environment that appears from theuser's point of view (e.g., content representing an external environmentthat may be provided to a user of a self-driving vehicle).

As shown in figure, the point cloud content may be generated based onthe capturing operation of one or more cameras. In this case, thecoordinate system may differ among the cameras, and accordingly thepoint cloud content providing system may calibrate one or more camerasto set a global coordinate system before the capturing operation. Inaddition, the point cloud content providing system may generate pointcloud content by synthesizing an arbitrary image and/or video with animage and/or video captured by the above-described capture technique.The point cloud content providing system may not perform the capturingoperation described in FIG. 3 when it generates point cloud contentrepresenting a virtual space. The point cloud content providing systemaccording to the embodiments may perform post-processing on the capturedimage and/or video. In other words, the point cloud content providingsystem may remove an unwanted area (for example, a background),recognize a space to which the captured images and/or videos areconnected, and, when there is a spatial hole, perform an operation offilling the spatial hole.

The point cloud content providing system may generate one piece of pointcloud content by performing coordinate transformation on points of thepoint cloud video secured from each camera. The point cloud contentproviding system may perform coordinate transformation on the pointsbased on the coordinates of the position of each camera. Accordingly,the point cloud content providing system may generate contentrepresenting one wide range, or may generate point cloud content havinga high density of points.

FIG. 4 illustrates an exemplary point cloud video encoder according toembodiments.

FIG. 4 shows an example of the point cloud video encoder 10002 of FIG. 1. The point cloud video encoder reconstructs and encodes point clouddata (e.g., positions and/or attributes of the points) to adjust thequality of the point cloud content (to, for example, lossless, lossy, ornear-lossless) according to the network condition or applications. Whenthe overall size of the point cloud content is large (e.g., point cloudcontent of 60 Gbps is given for 30 fps), the point cloud contentproviding system may fail to stream the content in real time.Accordingly, the point cloud content providing system may reconstructthe point cloud content based on the maximum target bitrate to providethe same in accordance with the network environment or the like. Asdescribed with reference to FIGS. 1 to 2 , the point cloud video encodermay perform geometry encoding and attribute encoding. The geometryencoding is performed before the attribute encoding.

The point cloud video encoder according to the embodiments includes acoordinate transformer (Transform coordinates) 40000, a quantizer(Quantize and remove points (voxelize)) 40001, an octree analyzer(Analyze octree) 40002, and a surface approximation analyzer (Analyzesurface approximation) 40003, an arithmetic encoder (Arithmetic encode)40004, a geometric reconstructor (Reconstruct geometry) 40005, a colortransformer (Transform colors) 40006, an attribute transformer(Transform attributes) 40007, a RAHT transformer (RAHT) 40008, an LODgenerator (Generate LOD) 40009, a lifting transformer (Lifting) 40010, acoefficient quantizer (Quantize coefficients) 40011, and/or anarithmetic encoder (Arithmetic encode) 40012.

The coordinate transformer 40000, the quantizer 40001, the octreeanalyzer 40002, the surface approximation analyzer 40003, the arithmeticencoder 40004, and the geometry reconstructor 40005 may perform geometryencoding. The geometry encoding according to the embodiments may includeoctree geometry coding, direct coding, trisoup geometry encoding, andentropy encoding. The direct coding and trisoup geometry encoding areapplied selectively or in combination. The geometry encoding is notlimited to the above-described example.

As shown in the figure, the coordinate transformer 40000 according tothe embodiments receives positions and transforms the same intocoordinates. For example, the positions may be transformed into positioninformation in a three-dimensional space (for example, athree-dimensional space represented by an XYZ coordinate system). Theposition information in the three-dimensional space according to theembodiments may be referred to as geometry information.

The quantizer 40001 according to the embodiments quantizes the geometryinformation. For example, the quantizer 40001 may quantize the pointsbased on a minimum position value of all points (for example, a minimumvalue on each of the X, Y, and Z axes). The quantizer 40001 performs aquantization operation of multiplying the difference between the minimumposition value and the position value of each point by a presetquantization scale value and then finding the nearest integer value byrounding the value obtained through the multiplication. Thus, one ormore points may have the same quantized position (or position value).The quantizer 40001 according to the embodiments performs voxelizationbased on the quantized positions to reconstruct quantized points. Thevoxelization means a minimum unit representing position information in3D space. Points of point cloud content (or 3D point cloud video)according to the embodiments may be included in one or more voxels. Theterm voxel, which is a compound of volume and pixel, refers to a 3Dcubic space generated when a 3D space is divided into units (unit=1.0)based on the axes representing the 3D space (e.g., X-axis, Y-axis, andZ-axis). The quantizer 40001 may match groups of points in the 3D spacewith voxels. According to embodiments, one voxel may include only onepoint. According to embodiments, one voxel may include one or morepoints. In order to express one voxel as one point, the position of thecenter point of a voxel may be set based on the positions of one or morepoints included in the voxel. In this case, attributes of all positionsincluded in one voxel may be combined and assigned to the voxel.

The octree analyzer 40002 according to the embodiments performs octreegeometry coding (or octree coding) to present voxels in an octreestructure. The octree structure represents points matched with voxels,based on the octal tree structure.

The surface approximation analyzer 40003 according to the embodimentsmay analyze and approximate the octree. The octree analysis andapproximation according to the embodiments is a process of analyzing aregion containing a plurality of points to efficiently provide octreeand voxelization.

The arithmetic encoder 40004 according to the embodiments performsentropy encoding on the octree and/or the approximated octree. Forexample, the encoding scheme includes arithmetic encoding. As a resultof the encoding, a geometry bitstream is generated.

The color transformer 40006, the attribute transformer 40007, the RAHTtransformer 40008, the LOD generator 40009, the lifting transformer40010, the coefficient quantizer 40011, and/or the arithmetic encoder40012 perform attribute encoding. As described above, one point may haveone or more attributes. The attribute encoding according to theembodiments is equally applied to the attributes that one point has.However, when an attribute (e.g., color) includes one or more elements,attribute encoding is independently applied to each element. Theattribute encoding according to the embodiments includes color transformcoding, attribute transform coding, region adaptive hierarchicaltransform (RAHT) coding, interpolation-based hierarchicalnearest-neighbor prediction (prediction transform) coding, andinterpolation-based hierarchical nearest-neighbor prediction with anupdate/lifting step (lifting transform) coding. Depending on the pointcloud content, the RAHT coding, the prediction transform coding and thelifting transform coding described above may be selectively used, or acombination of one or more of the coding schemes may be used. Theattribute encoding according to the embodiments is not limited to theabove-described example.

The color transformer 40006 according to the embodiments performs colortransform coding of transforming color values (or textures) included inthe attributes. For example, the color transformer 40006 may transformthe format of color information (for example, from RGB to YCbCr). Theoperation of the color transformer 40006 according to embodiments may beoptionally applied according to the color values included in theattributes.

The geometry reconstructor 40005 according to the embodimentsreconstructs (decompresses) the octree and/or the approximated octree.The geometry reconstructor 40005 reconstructs the octree/voxels based onthe result of analyzing the distribution of points. The reconstructedoctree/voxels may be referred to as reconstructed geometry (restoredgeometry).

The attribute transformer 40007 according to the embodiments performsattribute transformation to transform the attributes based on thereconstructed geometry and/or the positions on which geometry encodingis not performed. As described above, since the attributes are dependenton the geometry, the attribute transformer 40007 may transform theattributes based on the reconstructed geometry information. For example,based on the position value of a point included in a voxel, theattribute transformer 40007 may transform the attribute of the point atthe position. As described above, when the position of the center of avoxel is set based on the positions of one or more points included inthe voxel, the attribute transformer 40007 transforms the attributes ofthe one or more points. When the trisoup geometry encoding is performed,the attribute transformer 40007 may transform the attributes based onthe trisoup geometry encoding.

The attribute transformer 40007 may perform the attribute transformationby calculating the average of attributes or attribute values ofneighboring points (e.g., color or reflectance of each point) within aspecific position/radius from the position (or position value) of thecenter of each voxel. The attribute transformer 40007 may apply a weightaccording to the distance from the center to each point in calculatingthe average. Accordingly, each voxel has a position and a calculatedattribute (or attribute value).

The attribute transformer 40007 may search for neighboring pointsexisting within a specific position/radius from the position of thecenter of each voxel based on the K-D tree or the Morton code. The K-Dtree is a binary search tree and supports a data structure capable ofmanaging points based on the positions such that nearest neighbor search(NNS) can be performed quickly. The Morton code is generated bypresenting coordinates (e.g., (x, y, z)) representing 3D positions ofall points as bit values and mixing the bits. For example, when thecoordinates representing the position of a point are (5, 9, 1), the bitvalues for the coordinates are (0101, 1001, 0001). Mixing the bit valuesaccording to the bit index in order of z, y, and x yields 010001000111.This value is expressed as a decimal number of 1095. That is, the Mortoncode value of the point having coordinates (5, 9, 1) is 1095. Theattribute transformer 40007 may order the points based on the Mortoncode values and perform NNS through a depth-first traversal process.After the attribute transformation operation, the K-D tree or the Mortoncode is used when the NNS is needed in another transformation processfor attribute coding.

As shown in the figure, the transformed attributes are input to the RAHTtransformer 40008 and/or the LOD generator 40009.

The RAHT transformer 40008 according to the embodiments performs RAHTcoding for predicting attribute information based on the reconstructedgeometry information. For example, the RAHT transformer 40008 maypredict attribute information of a node at a higher level in the octreebased on the attribute information associated with a node at a lowerlevel in the octree.

The LOD generator 40009 according to the embodiments generates a levelof detail (LOD). The LOD according to the embodiments is a degree ofdetail of point cloud content. As the LOD value decrease, it indicatesthat the detail of the point cloud content is degraded. As the LOD valueincreases, it indicates that the detail of the point cloud content isenhanced. Points may be classified by the LOD.

The lifting transformer 40010 according to the embodiments performslifting transform coding of transforming the attributes a point cloudbased on weights. As described above, lifting transform coding may beoptionally applied.

The coefficient quantizer 40011 according to the embodiments quantizesthe attribute-coded attributes based on coefficients.

The arithmetic encoder 40012 according to the embodiments encodes thequantized attributes based on arithmetic coding.

Although not shown in the figure, the elements of the point cloud videoencoder of FIG. 4 may be implemented by hardware including one or moreprocessors or integrated circuits configured to communicate with one ormore memories included in the point cloud content providing apparatus,software, firmware, or a combination thereof. The one or more processorsmay perform at least one of the operations and/or functions of theelements of the point cloud video encoder of FIG. 4 described above.Additionally, the one or more processors may operate or execute a set ofsoftware programs and/or instructions for performing the operationsand/or functions of the elements of the point cloud video encoder ofFIG. 4 . The one or more memories according to the embodiments mayinclude a high speed random access memory, or include a non-volatilememory (e.g., one or more magnetic disk storage devices, flash memorydevices, or other non-volatile solid-state memory devices).

FIG. 5 shows an example of voxels according to embodiments.

FIG. 5 shows voxels positioned in a 3D space represented by a coordinatesystem composed of three axes, which are the X-axis, the Y-axis, and theZ-axis. As described with reference to FIG. 4 , the point cloud videoencoder (e.g., the quantizer 40001) may perform voxelization. Voxelrefers to a 3D cubic space generated when a 3D space is divided intounits (unit=1.0) based on the axes representing the 3D space (e.g.,X-axis, Y-axis, and Z-axis). FIG. 5 shows an example of voxels generatedthrough an octree structure in which a cubical axis-aligned bounding boxdefined by two poles (0, 0, 0) and (2^(d), 2^(d), 2^(d)) is recursivelysubdivided. One voxel includes at least one point. The spatialcoordinates of a voxel may be estimated from the positional relationshipwith a voxel group. As described above, a voxel has an attribute (suchas color or reflectance) like pixels of a 2D image/video. The details ofthe voxel are the same as those described with reference to FIG. 4 , andtherefore a description thereof is omitted.

FIG. 6 shows an example of an octree and occupancy code according toembodiments.

As described with reference to FIGS. 1 to 4 , the point cloud contentproviding system (point cloud video encoder 10002) or the octreeanalyzer 40002 of the point cloud video encoder performs octree geometrycoding (or octree coding) based on an octree structure to efficientlymanage the region and/or position of the voxel.

The upper part of FIG. 6 shows an octree structure. The 3D space of thepoint cloud content according to the embodiments is represented by axes(e.g., X-axis, Y-axis, and Z-axis) of the coordinate system. The octreestructure is created by recursive subdividing of a cubical axis-alignedbounding box defined by two poles (0, 0, 0) and (2^(d), 2^(d), 2^(d)).Here, 2^(d) may be set to a value constituting the smallest bounding boxsurrounding all points of the point cloud content (or point cloudvideo). Here, d denotes the depth of the octree. The value of d isdetermined in Equation 1. In Equation 1, (x^(int) _(n), y^(int) _(n),z^(int) _(n)) denotes the positions (or position values) of quantizedpoints.

d=Ceil(Log 2(Max(x _(n) ^(int) ,y _(n) ^(int) ,z _(n) ^(int) ,n=1, . . .,N)+1)  Equation 1

As shown in the middle of the upper part of FIG. 6 , the entire 3D spacemay be divided into eight spaces according to partition. Each dividedspace is represented by a cube with six faces. As shown in the upperright of FIG. 6 , each of the eight spaces is divided again based on theaxes of the coordinate system (e.g., X-axis, Y-axis, and Z-axis).Accordingly, each space is divided into eight smaller spaces. Thedivided smaller space is also represented by a cube with six faces. Thispartitioning scheme is applied until the leaf node of the octree becomesa voxel.

The lower part of FIG. 6 shows an octree occupancy code. The occupancycode of the octree is generated to indicate whether each of the eightdivided spaces generated by dividing one space contains at least onepoint. Accordingly, a single occupancy code is represented by eightchild nodes. Each child node represents the occupancy of a dividedspace, and the child node has a value in 1 bit. Accordingly, theoccupancy code is represented as an 8-bit code. That is, when at leastone point is contained in the space corresponding to a child node, thenode is assigned a value of 1. When no point is contained in the spacecorresponding to the child node (the space is empty), the node isassigned a value of 0. Since the occupancy code shown in FIG. 6 is00100001, it indicates that the spaces corresponding to the third childnode and the eighth child node among the eight child nodes each containat least one point. As shown in the figure, each of the third child nodeand the eighth child node has eight child nodes, and the child nodes arerepresented by an 8-bit occupancy code. The figure shows that theoccupancy code of the third child node is 10000111, and the occupancycode of the eighth child node is 01001111. The point cloud video encoder(for example, the arithmetic encoder 40004) according to the embodimentsmay perform entropy encoding on the occupancy codes. In order toincrease the compression efficiency, the point cloud video encoder mayperform intra/inter-coding on the occupancy codes. The reception device(for example, the reception device 10004 or the point cloud videodecoder 10006) according to the embodiments reconstructs the octreebased on the occupancy codes.

The point cloud video encoder (for example, the octree analyzer 40002)according to the embodiments may perform voxelization and octree codingto store the positions of points. However, points are not always evenlydistributed in the 3D space, and accordingly there may be a specificregion in which fewer points are present. Accordingly, it is inefficientto perform voxelization for the entire 3D space. For example, when aspecific region contains few points, voxelization does not need to beperformed in the specific region.

Accordingly, for the above-described specific region (or a node otherthan the leaf node of the octree), the point cloud video encoderaccording to the embodiments may skip voxelization and perform directcoding to directly code the positions of points included in the specificregion. The coordinates of a direct coding point according to theembodiments are referred to as direct coding mode (DCM). The point cloudvideo encoder according to the embodiments may also perform trisoupgeometry encoding, which is to reconstruct the positions of the pointsin the specific region (or node) based on voxels, based on a surfacemodel. The trisoup geometry encoding is geometry encoding thatrepresents an object as a series of triangular meshes. Accordingly, thepoint cloud video decoder may generate a point cloud from the meshsurface. The direct coding and trisoup geometry encoding according tothe embodiments may be selectively performed. In addition, the directcoding and trisoup geometry encoding according to the embodiments may beperformed in combination with octree geometry coding (or octree coding).

To perform direct coding, the option to use the direct mode for applyingdirect coding should be activated. Anode to which direct coding is to beapplied is not a leaf node, and points less than a threshold should bepresent within a specific node. In addition, the total number of pointsto which direct coding is to be applied should not exceed a presetthreshold. When the conditions above are satisfied, the point cloudvideo encoder (or the arithmetic encoder 40004) according to theembodiments may perform entropy coding on the positions (or positionvalues) of the points.

The point cloud video encoder (for example, the surface approximationanalyzer 40003) according to the embodiments may determine a specificlevel of the octree (a level less than the depth d of the octree), andthe surface model may be used staring with that level to perform trisoupgeometry encoding to reconstruct the positions of points in the regionof the node based on voxels (Trisoup mode). The point cloud videoencoder according to the embodiments may specify a level at whichtrisoup geometry encoding is to be applied. For example, when thespecific level is equal to the depth of the octree, the point cloudvideo encoder does not operate in the trisoup mode. In other words, thepoint cloud video encoder according to the embodiments may operate inthe trisoup mode only when the specified level is less than the value ofdepth of the octree. The 3D cube region of the nodes at the specifiedlevel according to the embodiments is called a block. One block mayinclude one or more voxels. The block or voxel may correspond to abrick. Geometry is represented as a surface within each block. Thesurface according to embodiments may intersect with each edge of a blockat most once.

One block has 12 edges, and accordingly there are at least 12intersections in one block. Each intersection is called a vertex (orapex). A vertex present along an edge is detected when there is at leastone occupied voxel adjacent to the edge among all blocks sharing theedge. The occupied voxel according to the embodiments refers to a voxelcontaining a point. The position of the vertex detected along the edgeis the average position along the edge of all voxels adjacent to theedge among all blocks sharing the edge.

Once the vertex is detected, the point cloud video encoder according tothe embodiments may perform entropy encoding on the starting point (x,y, z) of the edge, the direction vector (Δx, Δy, Δz) of the edge, andthe vertex position value (relative position value within the edge).When the trisoup geometry encoding is applied, the point cloud videoencoder according to the embodiments (for example, the geometryreconstructor 40005) may generate restored geometry (reconstructedgeometry) by performing the triangle reconstruction, up-sampling, andvoxelization processes.

The vertices positioned at the edge of the block determine a surfacethat passes through the block. The surface according to the embodimentsis a non-planar polygon. In the triangle reconstruction process, asurface represented by a triangle is reconstructed based on the startingpoint of the edge, the direction vector of the edge, and the positionvalues of the vertices. The triangle reconstruction process is performedaccording to Equation 2 by: i) calculating the centroid value of eachvertex, ii) subtracting the center value from each vertex value, andiii) estimating the sum of the squares of the values obtained by thesubtraction.

$\begin{matrix}{{Equation}2} &  \\{\begin{bmatrix}\mu_{x} \\\mu_{y} \\\mu_{z}\end{bmatrix} = {\frac{1}{n}{{\sum}_{i = 1}^{n}\begin{bmatrix}x_{i} \\y_{i} \\z_{i}\end{bmatrix}}}} & \end{matrix}$ $\begin{matrix}{\begin{bmatrix}{\overset{\_}{x}}_{i} \\{\overset{\_}{y}}_{i} \\{\overset{\_}{z}}_{i}\end{bmatrix} = {\begin{bmatrix}x_{i} \\y_{i} \\z_{i}\end{bmatrix} - \begin{bmatrix}\mu_{x} \\\mu_{y} \\\mu_{z}\end{bmatrix}}} & \end{matrix}$ $\begin{matrix}{\begin{bmatrix}\sigma_{x}^{2} \\\sigma_{y}^{2} \\\sigma_{z}^{2}\end{bmatrix} = {{\sum}_{i = 1}^{n}\begin{bmatrix}{\overset{\_}{x}}_{i}^{2} \\{\overset{\_}{y}}_{i}^{2} \\{\overset{\_}{z}}_{i}^{2}\end{bmatrix}}} & \end{matrix}$

Then, the minimum value of the sum is estimated, and the projectionprocess is performed according to the axis with the minimum value. Forexample, when the element x is the minimum, each vertex is projected onthe x-axis with respect to the center of the block, and projected on the(y, z) plane. When the values obtained through projection on the (y, z)plane are (ai, bi), the value of θ is estimated through atan 2(bi, ai),and the vertices are ordered based on the value of θ. The table 1 belowshows a combination of vertices for creating a triangle according to thenumber of the vertices. The vertices are ordered from 1 to n. The table1 below shows that for four vertices, two triangles may be constructedaccording to combinations of vertices. The first triangle may consist ofvertices 1, 2, and 3 among the ordered vertices, and the second trianglemay consist of vertices 3, 4, and 1 among the ordered vertices.

TABLE 1 Triangles formed from vertices ordered 1, . . . , n n Triangles3 (1, 2, 3) 4 (1, 2, 3), (3, 4, 1) 5 (1, 2, 3), (3, 4, 5), (5, 1, 3) 6(1, 2, 3), (3, 4, 5), (5, 6, 1), (1, 3, 5) 7 (1, 2, 3), (3, 4, 5), (5,6, 7), (7, 1, 3), (3, 5, 7) 8 (1, 2, 3), (3, 4, 5), (5, 6, 7), (7, 8,1), (1, 3, 5), (5, 7, 1) 9 (1, 2, 3), (3, 4, 5), (5, 6, 7), (7, 8, 9),(9, 1, 3), (3, 5, 7), (7, 9, 3) 10 (1, 2, 3), (3, 4, 5), (5, 6, 7), (7,8, 9), (9, 10, 1), (1, 3, 5), (5, 7, 9), (9, 1, 5) 11 (1, 2, 3), (3, 4,5), (5, 6, 7), (7, 8, 9), (9, 10, 11), (11, 1, 3), (3, 5, 7), (7, 9,11), (11, 3, 7) 12 (1, 2, 3), (3, 4, 5), (5, 6, 7), (7, 8, 9), (9, 10,11), (11, 12, 1), (1, 3, 5), (5, 7, 9), (9, 11, 1), (1, 5, 9)

The upsampling process is performed to add points in the middle alongthe edge of the triangle and perform voxelization. The added points aregenerated based on the upsampling factor and the width of the block. Theadded points are called refined vertices. The point cloud video encoderaccording to the embodiments may voxelize the refined vertices. Inaddition, the point cloud video encoder may perform attribute encodingbased on the voxelized positions (or position values).

FIG. 7 shows an example of a neighbor node pattern according toembodiments.

In order to increase the compression efficiency of the point cloudvideo, the point cloud video encoder according to the embodiments mayperform entropy coding based on context adaptive arithmetic coding.

As described with reference to FIGS. 1 to 6 , the point cloud contentproviding system or the point cloud video encoder 10002 of FIG. 1 , orthe point cloud video encoder or arithmetic encoder 40004 of FIG. 4 mayperform entropy coding on the occupancy code immediately. In addition,the point cloud content providing system or the point cloud videoencoder may perform entropy encoding (intra encoding) based on theoccupancy code of the current node and the occupancy of neighboringnodes, or perform entropy encoding (inter encoding) based on theoccupancy code of the previous frame. A frame according to embodimentsrepresents a set of point cloud videos generated at the same time. Thecompression efficiency of intra encoding/inter encoding according to theembodiments may depend on the number of neighboring nodes that arereferenced. When the bits increase, the operation becomes complicated,but the encoding may be biased to one side, which may increase thecompression efficiency. For example, when a 3-bit context is given,coding needs to be performed using 23=8 methods. The part divided forcoding affects the complexity of implementation. Accordingly, it isnecessary to meet an appropriate level of compression efficiency andcomplexity.

FIG. 7 illustrates a process of obtaining an occupancy pattern based onthe occupancy of neighbor nodes. The point cloud video encoder accordingto the embodiments determines occupancy of neighbor nodes of each nodeof the octree and obtains a value of a neighbor pattern. The neighbornode pattern is used to infer the occupancy pattern of the node. The uppart of FIG. 7 shows a cube corresponding to a node (a cube positionedin the middle) and six cubes (neighbor nodes) sharing at least one facewith the cube. The nodes shown in the figure are nodes of the samedepth. The numbers shown in the figure represent weights (1, 2, 4, 8,16, and 32) associated with the six nodes, respectively. The weights areassigned sequentially according to the positions of neighboring nodes.

The down part of FIG. 7 shows neighbor node pattern values. A neighbornode pattern value is the sum of values multiplied by the weight of anoccupied neighbor node (a neighbor node having a point). Accordingly,the neighbor node pattern values are 0 to 63. When the neighbor nodepattern value is 0, it indicates that there is no node having a point(no occupied node) among the neighbor nodes of the node. When theneighbor node pattern value is 63, it indicates that all neighbor nodesare occupied nodes. As shown in the figure, since neighbor nodes towhich weights 1, 2, 4, and 8 are assigned are occupied nodes, theneighbor node pattern value is 15, the sum of 1, 2, 4, and 8. The pointcloud video encoder may perform coding according to the neighbor nodepattern value (for example, when the neighbor node pattern value is 63,64 kinds of coding may be performed). According to embodiments, thepoint cloud video encoder may reduce coding complexity by changing aneighbor node pattern value (for example, based on a table by which 64is changed to 10 or 6).

FIG. 8 illustrates an example of point configuration in each LODaccording to embodiments.

As described with reference to FIGS. 1 to 7 , encoded geometry isreconstructed (decompressed) before attribute encoding is performed.When direct coding is applied, the geometry reconstruction operation mayinclude changing the placement of direct coded points (e.g., placing thedirect coded points in front of the point cloud data). When trisoupgeometry encoding is applied, the geometry reconstruction process isperformed through triangle reconstruction, up-sampling, andvoxelization. Since the attribute depends on the geometry, attributeencoding is performed based on the reconstructed geometry.

The point cloud video encoder (for example, the LOD generator 40009) mayclassify (reorganize or group) points by LOD. Figure shows the pointcloud content corresponding to LODs. The leftmost picture in figurerepresents original point cloud content. The second picture from theleft of figure represents distribution of the points in the lowest LOD,and the rightmost picture in figure represents distribution of thepoints in the highest LOD. That is, the points in the lowest LOD aresparsely distributed, and the points in the highest LOD are denselydistributed. That is, as the LOD rises in the direction pointed by thearrow indicated at the bottom of figure, the space (or distance) betweenpoints is narrowed.

FIG. 9 illustrates an example of point configuration for each LODaccording to embodiments.

As described with reference to FIGS. 1 to 8 , the point cloud contentproviding system, or the point cloud video encoder (for example, thepoint cloud video encoder 10002 of FIG. 1 , the point cloud videoencoder of FIG. 4 , or the LOD generator 40009) may generates an LOD.The LOD is generated by reorganizing the points into a set of refinementlevels according to a set LOD distance value (or a set of Euclideandistances). The LOD generation process is performed not only by thepoint cloud video encoder, but also by the point cloud video decoder.

The upper part of FIG. 9 shows examples (P0 to P9) of points of thepoint cloud content distributed in a 3D space. In FIG. 9 , the originalorder represents the order of points P0 to P9 before LOD generation. InFIG. 9 , the LOD based order represents the order of points according tothe LOD generation. Points are reorganized by LOD. Also, a high LODcontains the points belonging to lower LODs. As shown in FIG. 9 , LOD0contains P0, P5, P4 and P2. LOD1 contains the points of LOD0, P1, P6 andP3. LOD2 contains the points of LOD0, the points of LOD1, P9, P8 and P7.

As described with reference to FIG. 4 , the point cloud video encoderaccording to the embodiments may perform prediction transform codingbased on LOD, lifting transform coding based on LOD, and RAHT transformcoding selectively or in combination.

The point cloud video encoder according to the embodiments may generatea predictor for points to perform prediction transform coding based onLOD for setting a predicted attribute (or predicted attribute value) ofeach point. That is, N predictors may be generated for N points. Thepredictor according to the embodiments may calculate a weight(=1/distance) based on the LOD value of each point, indexing informationabout neighboring points present within a set distance for each LOD, anda distance to the neighboring points.

The predicted attribute (or attribute value) according to theembodiments is set to the average of values obtained by multiplying theattributes (or attribute values) (e.g., color, reflectance, etc.) ofneighbor points set in the predictor of each point by a weight (orweight value) calculated based on the distance to each neighbor point.The point cloud video encoder according to the embodiments (for example,the coefficient quantizer 40011) may quantize and inversely quantize theresidual of each point (which may be called residual attribute, residualattribute value, attribute prediction residual value or prediction errorattribute value and so on) obtained by subtracting a predicted attribute(or attribute value) each point from the attribute (i.e., originalattribute value) of each point. The quantization process performed for aresidual attribute value in a transmission device is configured as shownin table 2. The inverse quantization process performed for a residualattribute value in a reception device is configured as shown in table 3.

TABLE 2 int PCCQuantization(int value, int quantStep) { if( value >=0) {return floor(value / quantStep + 1.0 / 3.0); } else { return−floor(−value / quantStep + 1.0 / 3.0); } }

TABLE 3 int PCCInverseQuantization(int value, int quantStep) { if(quantStep ==0) { return value; } else { return value * quantStep; } }

When the predictor of each point has neighbor points, the point cloudvideo encoder (e.g., the arithmetic encoder 40012) according to theembodiments may perform entropy coding on the quantized and inverselyquantized residual attribute values (or residual values) as describedabove. When the predictor of each point has no neighbor point, the pointcloud video encoder according to the embodiments (for example, thearithmetic encoder 40012) may perform entropy coding on the attributesof the corresponding point without performing the above-describedoperation.

The point cloud video encoder according to the embodiments (for example,the lifting transformer 40010) may generate a predictor of each point,set the calculated LOD and register neighbor points in the predictor,and set weights according to the distances to neighbor points to performlifting transform coding. The lifting transform coding according to theembodiments is similar to the above-described prediction transformcoding, but differs therefrom in that weights are cumulatively appliedto attribute values. The process of cumulatively applying weights to theattribute values according to embodiments is configured as follows.

-   -   1) Create an array Quantization Weight (QW) for storing the        weight value of each point. The initial value of all elements of        QW is 1.0. Multiply the QW values of the predictor indexes of        the neighbor nodes registered in the predictor by the weight of        the predictor of the current point, and add the values obtained        by the multiplication.    -   2) Lift prediction process: Subtract the value obtained by        multiplying the attribute value of the point by the weight from        the existing attribute value to calculate a predicted attribute        value.    -   3) Create temporary arrays called update weight and update and        initialize the temporary arrays to zero.    -   4) Cumulatively add the weights calculated by multiplying the        weights calculated for all predictors by a weight stored in the        QW corresponding to a predictor index to the update weight array        as indexes of neighbor nodes. Cumulatively add, to the update        array, a value obtained by multiplying the attribute value of        the index of a neighbor node by the calculated weight.    -   5) Lift update process: Divide the attribute values of the        update array for all predictors by the weight value of the        update weight array of the predictor index, and add the existing        attribute value to the values obtained by the division.    -   6) Calculate predicted attributes by multiplying the attribute        values updated through the lift update process by the weight        updated through the lift prediction process (stored in the QW)        for all predictors. The point cloud video encoder (e.g.,        coefficient quantizer 40011) according to the embodiments        quantizes the predicted attribute values. In addition, the point        cloud video encoder (e.g., the arithmetic encoder 40012)        performs entropy coding on the quantized attribute values.

The point cloud video encoder (for example, the RAHT transformer 40008)according to the embodiments may perform RAHT transform coding in whichattributes of nodes of a higher level are predicted using the attributesassociated with nodes of a lower level in the octree. RAHT transformcoding is an example of attribute intra coding through an octreebackward scan. The point cloud video encoder according to theembodiments scans the entire region from the voxel and repeats themerging process of merging the voxels into a larger block at each stepuntil the root node is reached. The merging process according to theembodiments is performed only on the occupied nodes. The merging processis not performed on the empty node. The merging process is performed onan upper node immediately above the empty node.

Equation 3 below represents a RAHT transformation matrix. In Equation 3,g_(l x,y,z) denotes the average attribute value of voxels at level l.g_(l x,y,z) may be calculated based on g_(l+1) _(2x,y,z) and g_(l+1)_(2x+1,y,z) . The weights for g_(l) _(2x,y,z) and g_(l) _(2x+1,y,z) arew1=w_(l) _(2x,y,z) and w2=w_(l) _(2x+1,y,z) .

$\begin{matrix}{\lceil \begin{matrix}g_{l - 1_{x,y,z}} \\h_{l - 1_{x,y,z}}\end{matrix} \rceil = {T_{w1w2}\lceil \begin{matrix}g_{l_{{2x},y,z}} \\g_{l_{{{2x} + 1},y,z}}\end{matrix} \rceil}} & {{Equation}3}\end{matrix}$ $T_{w1w2} = {\frac{1}{\sqrt{{w1} + {w2}}}\begin{bmatrix}\sqrt{w1} & \sqrt{w2} \\{- \sqrt{w2}} & \sqrt{w1}\end{bmatrix}}$

Here, g_(l-1) _(x,y,z) is a low-pass value and is used in the mergingprocess at the next higher level. h_(l-1) _(x,y,z) denotes high-passcoefficients. The high-pass coefficients at each step are quantized andsubjected to entropy coding (for example, encoding by the arithmeticencoder 40012). The weights are calculated as w_(l-1) _(x,y,z) =w_(l)_(2x,y,z) +w_(l) _(2x+1,y,z) . The root node is created through the g₀_(0,0,0) and g₁ _(0,0,1) as Equation 4.

$\begin{matrix}{\lceil \begin{matrix}g^{DC} \\h_{0_{0,0,0}}\end{matrix} \rceil = {T_{w1000w1001}\lceil \begin{matrix}g_{1_{0,0,{0z}}} \\g_{1_{0,0,1}}\end{matrix} \rceil}} & {{Equation}4}\end{matrix}$

The value of gDC is also quantized and subjected to entropy coding likethe high-pass coefficients.

FIG. 10 illustrates a point cloud video decoder according toembodiments.

The point cloud video decoder illustrated in FIG. 10 is an example ofthe point cloud video decoder 10006 described in FIG. 1 , and mayperform the same or similar operations as the operations of the pointcloud video decoder 10006 illustrated in FIG. 1 . As shown in thefigure, the point cloud video decoder may receive a geometry bitstreamand an attribute bitstream contained in one or more bitstreams. Thepoint cloud video decoder includes a geometry decoder and an attributedecoder. The geometry decoder performs geometry decoding on the geometrybitstream and outputs decoded geometry. The attribute decoder performsattribute decoding on the attribute bitstream based on the decodedgeometry, and outputs decoded attributes. The decoded geometry anddecoded attributes are used to reconstruct point cloud content (adecoded point cloud).

FIG. 11 illustrates a point cloud video decoder according toembodiments.

The point cloud video decoder illustrated in FIG. 11 is an example ofthe point cloud video decoder illustrated in FIG. 10 , and may perform adecoding operation, which is an inverse process of the encodingoperation of the point cloud video encoder illustrated in FIGS. 1 to 9 .

As described with reference to FIGS. 1 and 10 , the point cloud videodecoder may perform geometry decoding and attribute decoding. Thegeometry decoding is performed before the attribute decoding.

The point cloud video decoder according to the embodiments includes anarithmetic decoder (Arithmetic decode) 11000, an octree synthesizer(Synthesize octree) 11001, a surface approximation synthesizer(Synthesize surface approximation) 11002, and a geometry reconstructor(Reconstruct geometry) 11003, a coordinate inverse transformer (Inversetransform coordinates) 11004, an arithmetic decoder (Arithmetic decode)11005, an inverse quantizer (Inverse quantize) 11006, a RAHT transformer11007, an LOD generator (Generate LOD) 11008, an inverse lifter (inverselifting) 11009, and/or a color inverse transformer (Inverse transformcolors) 11010.

The arithmetic decoder 11000, the octree synthesizer 11001, the surfaceapproximation synthesizer 11002, and the geometry reconstructor 11003,and the coordinate inverse transformer 11004 may perform geometrydecoding. The geometry decoding according to the embodiments may includedirect decoding and trisoup geometry decoding. The direct decoding andtrisoup geometry decoding are selectively applied. The geometry decodingis not limited to the above-described example, and is performed as aninverse process of the geometry encoding described with reference toFIGS. 1 to 9 .

The arithmetic decoder 11000 according to the embodiments decodes thereceived geometry bitstream based on the arithmetic coding. Theoperation of the arithmetic decoder 11000 corresponds to the inverseprocess of the arithmetic encoder 40004.

The octree synthesizer 11001 according to the embodiments may generatean octree by acquiring an occupancy code from the decoded geometrybitstream (or information on the geometry secured as a result ofdecoding). The occupancy code is configured as described in detail withreference to FIGS. 1 to 9 .

When the trisoup geometry encoding is applied, the surface approximationsynthesizer 11002 according to the embodiments may synthesize a surfacebased on the decoded geometry and/or the generated octree.

The geometry reconstructor 11003 according to the embodiments mayregenerate geometry based on the surface and/or the decoded geometry. Asdescribed with reference to FIGS. 1 to 9 , direct coding and trisoupgeometry encoding are selectively applied. Accordingly, the geometryreconstructor 11003 directly imports and adds position information aboutthe points to which direct coding is applied. When the trisoup geometryencoding is applied, the geometry reconstructor 11003 may reconstructthe geometry by performing the reconstruction operations of the geometryreconstructor 40005, for example, triangle reconstruction, up-sampling,and voxelization. Details are the same as those described with referenceto FIG. 6 , and thus description thereof is omitted. The reconstructedgeometry may include a point cloud picture or frame that does notcontain attributes.

The coordinate inverse transformer 11004 according to the embodimentsmay acquire positions of the points by transforming the coordinatesbased on the reconstructed geometry.

The arithmetic decoder 11005, the inverse quantizer 11006, the RAHTtransformer 11007, the LOD generator 11008, the inverse lifter 11009,and/or the color inverse transformer 11010 may perform the attributedecoding described with reference to FIG. 10 . The attribute decodingaccording to the embodiments includes region adaptive hierarchicaltransform (RAHT) decoding, interpolation-based hierarchicalnearest-neighbor prediction (prediction transform) decoding, andinterpolation-based hierarchical nearest-neighbor prediction with anupdate/lifting step (lifting transform) decoding. The three decodingschemes described above may be used selectively, or a combination of oneor more decoding schemes may be used. The attribute decoding accordingto the embodiments is not limited to the above-described example.

The arithmetic decoder 11005 according to the embodiments decodes theattribute bitstream by arithmetic coding.

The inverse quantizer 11006 according to the embodiments inverselyquantizes the information about the decoded attribute bitstream orattributes secured as a result of the decoding, and outputs theinversely quantized attributes (or attribute values). The inversequantization may be selectively applied based on the attribute encodingof the point cloud video encoder.

According to embodiments, the RAHT transformer 11007, the LOD generator11008, and/or the inverse lifter 11009 may process the reconstructedgeometry and the inversely quantized attributes. As described above, theRAHT transformer 11007, the LOD generator 11008, and/or the inverselifter 11009 may selectively perform a decoding operation correspondingto the encoding of the point cloud video encoder.

The color inverse transformer 11010 according to the embodimentsperforms inverse transform coding to inversely transform a color value(or texture) included in the decoded attributes. The operation of thecolor inverse transformer 11010 may be selectively performed based onthe operation of the color transformer 40006 of the point cloud videoencoder.

Although not shown in the figure, the elements of the point cloud videodecoder of FIG. 11 may be implemented by hardware including one or moreprocessors or integrated circuits configured to communicate with one ormore memories included in the point cloud content providing apparatus,software, firmware, or a combination thereof. The one or more processorsmay perform at least one or more of the operations and/or functions ofthe elements of the point cloud video decoder of FIG. 11 describedabove. Additionally, the one or more processors may operate or execute aset of software programs and/or instructions for performing theoperations and/or functions of the elements of the point cloud videodecoder of FIG. 11 .

FIG. 12 illustrates a transmission device according to embodiments.

The transmission device shown in FIG. 12 is an example of thetransmission device 10000 of FIG. 1 (or the point cloud video encoder ofFIG. 4 ). The transmission device illustrated in FIG. 12 may perform oneor more of the operations and methods the same as or similar to those ofthe point cloud video encoder described with reference to FIGS. 1 to 9 .The transmission device according to the embodiments may include a datainput unit 12000, a quantization processor 12001, a voxelizationprocessor 12002, an octree occupancy code generator 12003, a surfacemodel processor 12004, an intra/inter-coding processor 12005, anarithmetic coder 12006, a metadata processor 12007, a color transformprocessor 12008, an attribute transform processor 12009, aprediction/lifting/RAHT transform processor 12010, an arithmetic coder12011 and/or a transmission processor 12012.

The data input unit 12000 according to the embodiments receives oracquires point cloud data. The data input unit 12000 may perform anoperation and/or acquisition method the same as or similar to theoperation and/or acquisition method of the point cloud video acquisitionunit 10001 (or the acquisition process 20000 described with reference toFIG. 2 ).

The data input unit 12000, the quantization processor 12001, thevoxelization processor 12002, the octree occupancy code generator 12003,the surface model processor 12004, the intra/inter-coding processor12005, and the arithmetic coder 12006 perform geometry encoding. Thegeometry encoding according to the embodiments is the same as or similarto the geometry encoding described with reference to FIGS. 1 to 9 , andthus a detailed description thereof is omitted.

The quantization processor 12001 according to the embodiments quantizesgeometry (e.g., position values of points). The operation and/orquantization of the quantization processor 12001 is the same as orsimilar to the operation and/or quantization of the quantizer 40001described with reference to FIG. 4 . Details are the same as thosedescribed with reference to FIGS. 1 to 9 .

The voxelization processor 12002 according to embodiments voxelizes thequantized position values of the points. The voxelization processor12002 may perform an operation and/or process the same or similar to theoperation and/or the voxelization process of the quantizer 40001described with reference to FIG. 4 . Details are the same as thosedescribed with reference to FIGS. 1 to 9 .

The octree occupancy code generator 12003 according to the embodimentsperforms octree coding on the voxelized positions of the points based onan octree structure. The octree occupancy code generator 12003 maygenerate an occupancy code. The octree occupancy code generator 12003may perform an operation and/or method the same as or similar to theoperation and/or method of the point cloud video encoder (or the octreeanalyzer 40002) described with reference to FIGS. 4 and 6 . Details arethe same as those described with reference to FIGS. 1 to 9 .

The surface model processor 12004 according to the embodiments mayperform trisoup geometry encoding based on a surface model toreconstruct the positions of points in a specific region (or node) on avoxel basis. The surface model processor 12004 may perform an operationand/or method the same as or similar to the operation and/or method ofthe point cloud video encoder (for example, the surface approximationanalyzer 40003) described with reference to FIG. 4 . Details are thesame as those described with reference to FIGS. 1 to 9 .

The intra/inter-coding processor 12005 according to the embodiments mayperform intra/inter-coding on point cloud data. The intra/inter-codingprocessor 12005 may perform coding the same as or similar to theintra/inter-coding described with reference to FIG. 7 . Details are thesame as those described with reference to FIG. 7 . According toembodiments, the intra/inter-coding processor 12005 may be included inthe arithmetic coder 12006.

The arithmetic coder 12006 according to the embodiments performs entropyencoding on an octree of the point cloud data and/or an approximatedoctree. For example, the encoding scheme includes arithmetic encoding.The arithmetic coder 12006 performs an operation and/or method the sameas or similar to the operation and/or method of the arithmetic encoder40004.

The metadata processor 12007 according to the embodiments processesmetadata about the point cloud data, for example, a set value, andprovides the same to a necessary processing process such as geometryencoding and/or attribute encoding. Also, the metadata processor 12007according to the embodiments may generate and/or process signalinginformation related to the geometry encoding and/or the attributeencoding. The signaling information according to the embodiments may beencoded separately from the geometry encoding and/or the attributeencoding. The signaling information according to the embodiments may beinterleaved.

The color transform processor 12008, the attribute transform processor12009, the prediction/lifting/RAHT transform processor 12010, and thearithmetic coder 12011 perform the attribute encoding. The attributeencoding according to the embodiments is the same as or similar to theattribute encoding described with reference to FIGS. 1 to 9 , and thus adetailed description thereof is omitted.

The color transform processor 12008 according to the embodimentsperforms color transform coding to transform color values included inattributes. The color transform processor 12008 may perform colortransform coding based on the reconstructed geometry. The reconstructedgeometry is the same as described with reference to FIGS. 1 to 9 . Also,it performs an operation and/or method the same as or similar to theoperation and/or method of the color transformer 40006 described withreference to FIG. 4 is performed. The detailed description thereof isomitted.

The attribute transform processor 12009 according to the embodimentsperforms attribute transformation to transform the attributes based onthe reconstructed geometry and/or the positions on which geometryencoding is not performed. The attribute transform processor 12009performs an operation and/or method the same as or similar to theoperation and/or method of the attribute transformer 40007 describedwith reference to FIG. 4 . The detailed description thereof is omitted.The prediction/lifting/RAHT transform processor 12010 according to theembodiments may code the transformed attributes by any one or acombination of RAHT coding, prediction transform coding, and liftingtransform coding. The prediction/lifting/RAHT transform processor 12010performs at least one of the operations the same as or similar to theoperations of the RAHT transformer 40008, the LOD generator 40009, andthe lifting transformer 40010 described with reference to FIG. 4 . Inaddition, the prediction transform coding, the lifting transform coding,and the RAHT transform coding are the same as those described withreference to FIGS. 1 to 9 , and thus a detailed description thereof isomitted.

The arithmetic coder 12011 according to the embodiments may encode thecoded attributes based on the arithmetic coding. The arithmetic coder12011 performs an operation and/or method the same as or similar to theoperation and/or method of the arithmetic encoder 40012.

The transmission processor 12012 according to the embodiments maytransmit each bitstream containing encoded geometry and/or encodedattributes and/or metadata (or referred to as metadata information), ortransmit one bitstream configured with the encoded geometry and/or theencoded attributes and/or the metadata. When the encoded geometry and/orthe encoded attributes and/or the metadata according to the embodimentsare configured into one bitstream, the bitstream may include one or moresub-bitstreams. The bitstream according to the embodiments may containsignaling information including a sequence parameter set (SPS) forsignaling of a sequence level, a geometry parameter set (GPS) forsignaling of geometry information coding, an attribute parameter set(APS) for signaling of attribute information coding, and a tileparameter set (TPS or tile inventory) for signaling of a tile level, andslice data. The slice data may include information about one or moreslices. One slice according to embodiments may include one geometrybitstream Geom0⁰ and one or more attribute bitstreams Attr0⁰ and Attr1⁰.The TPS (or tile inventory) according to the embodiments may includeinformation about each tile (for example, coordinate information andheight/size information about a bounding box) for one or more tiles. Thegeometry bitstream may contain a header and a payload. The header of thegeometry bitstream according to the embodiments may contain a parameterset identifier (geom_parameter_set_id), a tile identifier (geom_tile_id)and a slice identifier (geom_slice_id) included in the GPS, andinformation about the data contained in the payload. As described above,the metadata processor 12007 according to the embodiments may generateand/or process the signaling information and transmit the same to thetransmission processor 12012. According to embodiments, the elements toperform geometry encoding and the elements to perform attribute encodingmay share data/information with each other as indicated by dotted lines.The transmission processor 12012 according to the embodiments mayperform an operation and/or transmission method the same as or similarto the operation and/or transmission method of the transmitter 10003.Details are the same as those described with reference to FIGS. 1 and 2, and thus a description thereof is omitted.

FIG. 13 illustrates a reception device according to embodiments.

The reception device illustrated in FIG. 13 is an example of thereception device 10004 of FIG. 1 (or the point cloud video decoder ofFIGS. 10 and 11 ). The reception device illustrated in FIG. 13 mayperform one or more of the operations and methods the same as or similarto those of the point cloud video decoder described with reference toFIGS. 1 to 11 .

The reception device according to the embodiment includes a receiver13000, a reception processor 13001, an arithmetic decoder 13002, anoccupancy code-based octree reconstruction processor 13003, a surfacemodel processor (triangle reconstruction, up-sampling, voxelization)13004, an inverse quantization processor 13005, a metadata parser 13006,an arithmetic decoder 13007, an inverse quantization processor 13008, aprediction/lifting/RAHT inverse transform processor 13009, a colorinverse transform processor 13010, and/or a renderer 13011. Each elementfor decoding according to the embodiments may perform an inverse processof the operation of a corresponding element for encoding according tothe embodiments.

The receiver 13000 according to the embodiments receives point clouddata. The receiver 13000 may perform an operation and/or receptionmethod the same as or similar to the operation and/or reception methodof the receiver 10005 of FIG. 1 . The detailed description thereof isomitted.

The reception processor 13001 according to the embodiments may acquire ageometry bitstream and/or an attribute bitstream from the received data.The reception processor 13001 may be included in the receiver 13000.

The arithmetic decoder 13002, the occupancy code-based octreereconstruction processor 13003, the surface model processor 13004, andthe inverse quantization processor 1305 may perform geometry decoding.The geometry decoding according to embodiments is the same as or similarto the geometry decoding described with reference to FIGS. 1 to 10 , andthus a detailed description thereof is omitted.

The arithmetic decoder 13002 according to the embodiments may decode thegeometry bitstream based on arithmetic coding. The arithmetic decoder13002 performs an operation and/or coding the same as or similar to theoperation and/or coding of the arithmetic decoder 11000.

The occupancy code-based octree reconstruction processor 13003 accordingto the embodiments may reconstruct an octree by acquiring an occupancycode from the decoded geometry bitstream (or information about thegeometry secured as a result of decoding). The occupancy code-basedoctree reconstruction processor 13003 performs an operation and/ormethod the same as or similar to the operation and/or octree generationmethod of the octree synthesizer 11001. When the trisoup geometryencoding is applied, the surface model processor 1302 according to theembodiments may perform trisoup geometry decoding and related geometryreconstruction (for example, triangle reconstruction, up-sampling,voxelization) based on the surface model method. The surface modelprocessor 1302 performs an operation the same as or similar to that ofthe surface approximation synthesizer 11002 and/or the geometryreconstructor 11003.

The inverse quantization processor 1305 according to the embodiments mayinversely quantize the decoded geometry.

The metadata parser 1306 according to the embodiments may parse metadatacontained in the received point cloud data, for example, a set value.The metadata parser 1306 may pass the metadata to geometry decodingand/or attribute decoding. The metadata is the same as that describedwith reference to FIG. 12 , and thus a detailed description thereof isomitted.

The arithmetic decoder 13007, the inverse quantization processor 13008,the prediction/lifting/RAHT inverse transform processor 13009 and thecolor inverse transform processor 13010 perform attribute decoding. Theattribute decoding is the same as or similar to the attribute decodingdescribed with reference to FIGS. 1 to 10 , and thus a detaileddescription thereof is omitted.

The arithmetic decoder 13007 according to the embodiments may decode theattribute bitstream by arithmetic coding. The arithmetic decoder 13007may decode the attribute bitstream based on the reconstructed geometry.The arithmetic decoder 13007 performs an operation and/or coding thesame as or similar to the operation and/or coding of the arithmeticdecoder 11005.

The inverse quantization processor 13008 according to the embodimentsmay inversely quantize the decoded attribute bitstream. The inversequantization processor 13008 performs an operation and/or method thesame as or similar to the operation and/or inverse quantization methodof the inverse quantizer 11006.

The prediction/lifting/RAHT inverse transformer 13009 according to theembodiments may process the reconstructed geometry and the inverselyquantized attributes. The prediction/lifting/RAHT inverse transformprocessor 1301 performs one or more of operations and/or decoding thesame as or similar to the operations and/or decoding of the RAHTtransformer 11007, the LOD generator 11008, and/or the inverse lifter11009. The color inverse transform processor 13010 according to theembodiments performs inverse transform coding to inversely transformcolor values (or textures) included in the decoded attributes. The colorinverse transform processor 13010 performs an operation and/or inversetransform coding the same as or similar to the operation and/or inversetransform coding of the color inverse transformer 11010. The renderer13011 according to the embodiments may render the point cloud data.

FIG. 14 shows an exemplary structure operatively connectable with amethod/device for transmitting and receiving point cloud data accordingto embodiments.

The structure of FIG. 14 represents a configuration in which at leastone of a server 17600, a robot 17100, a self-driving vehicle 17200, anXR device 17300, a smartphone 17400, a home appliance 17500, and/or ahead-mount display (HMD) 17700 is connected to a cloud network 17000.The robot 17100, the self-driving vehicle 17200, the XR device 17300,the smartphone 17400, or the home appliance 17500 is referred to as adevice. In addition, the XR device 17300 may correspond to a point cloudcompressed data (PCC) device according to embodiments or may beoperatively connected to the PCC device.

The cloud network 17000 may represent a network that constitutes part ofthe cloud computing infrastructure or is present in the cloud computinginfrastructure. Here, the cloud network 17000 may be configured using a3G network, 4G or Long Term Evolution (LTE) network, or a 5G network.

The server 17600 may be connected to at least one of the robot 17100,the self-driving vehicle 17200, the XR device 17300, the smartphone17400, the home appliance 17500, and/or the HMD 17700 over the cloudnetwork 17000 and may assist in at least a part of the processing of theconnected devices 17100 to 17700.

The HMD 17700 represents one of the implementation types of the XRdevice and/or the PCC device according to the embodiments. The HMD typedevice according to the embodiments includes a communication unit, acontrol unit, a memory, an I/O unit, a sensor unit, and a power supplyunit.

Hereinafter, various embodiments of the devices 17100 to 17500 to whichthe above-described technology is applied will be described. The devices17100 to 17500 illustrated in FIG. 14 may be operativelyconnected/coupled to a point cloud data transmission device andreception according to the above-described embodiments.

<PCC+XR>

The XR/PCC device 17300 may employ PCC technology and/or XR (AR+VR)technology, and may be implemented as an HMD, a head-up display (HUD)provided in a vehicle, a television, a mobile phone, a smartphone, acomputer, a wearable device, a home appliance, a digital signage, avehicle, a stationary robot, or a mobile robot.

The XR/PCC device 17300 may analyze 3D point cloud data or image dataacquired through various sensors or from an external device and generateposition data and attribute data about 3D points. Thereby, the XR/PCCdevice 17300 may acquire information about the surrounding space or areal object, and render and output an XR object. For example, the XR/PCCdevice 17300 may match an XR object including auxiliary informationabout a recognized object with the recognized object and output thematched XR object.

<PCC+Self-driving+XR>

The self-driving vehicle 17200 may be implemented as a mobile robot, avehicle, an unmanned aerial vehicle, or the like by applying the PCCtechnology and the XR technology.

The self-driving vehicle 17200 to which the XR/PCC technology is appliedmay represent a self-driving vehicle provided with means for providingan XR image, or a self-driving vehicle that is a target ofcontrol/interaction in the XR image. In particular, the self-drivingvehicle 17200 which is a target of control/interaction in the XR imagemay be distinguished from the XR device 17300 and may be operativelyconnected thereto.

The self-driving vehicle 17200 having means for providing an XR/PCCimage may acquire sensor information from sensors including a camera,and output the generated XR/PCC image based on the acquired sensorinformation. For example, the self-driving vehicle 17200 may have an HUDand output an XR/PCC image thereto, thereby providing an occupant withan XR/PCC object corresponding to a real object or an object present onthe screen.

When the XR/PCC object is output to the HUD, at least a part of theXR/PCC object may be output to overlap the real object to which theoccupant's eyes are directed. On the other hand, when the XR/PCC objectis output on a display provided inside the self-driving vehicle, atleast a part of the XR/PCC object may be output to overlap an object onthe screen. For example, the self-driving vehicle 17200 may outputXR/PCC objects corresponding to objects such as a road, another vehicle,a traffic light, a traffic sign, a two-wheeled vehicle, a pedestrian,and a building.

The virtual reality (VR) technology, the augmented reality (AR)technology, the mixed reality (MR) technology and/or the point cloudcompression (PCC) technology according to the embodiments are applicableto various devices.

In other words, the VR technology is a display technology that providesonly CG images of real-world objects, backgrounds, and the like. On theother hand, the AR technology refers to a technology that shows avirtually created CG image on the image ofa real object. The MRtechnology is similar to the AR technology described above in thatvirtual objects to be shown are mixed and combined with the real world.However, the MR technology differs from the AR technology in that the ARtechnology makes a clear distinction between a real object and a virtualobject created as a CG image and uses virtual objects as complementaryobjects for real objects, whereas the MR technology treats virtualobjects as objects having equivalent characteristics as real objects.More specifically, an example of MR technology applications is ahologram service.

Recently, the VR, AR, and MR technologies are sometimes referred to asextended reality (XR) technology rather than being clearly distinguishedfrom each other. Accordingly, embodiments of the present disclosure areapplicable to any of the VR, AR, MR, and XR technologies. Theencoding/decoding based on PCC, V-PCC, and G-PCC techniques isapplicable to such technologies.

The PCC method/device according to the embodiments may be applied to avehicle that provides a self-driving service.

A vehicle that provides the self-driving service is connected to a PCCdevice for wired/wireless communication.

When the point cloud compression data (PCC) transmission/receptiondevice according to the embodiments is connected to a vehicle forwired/wireless communication, the device may receive/process contentdata related to an AR/VR/PCC service, which may be provided togetherwith the self-driving service, and transmit the same to the vehicle. Inthe case where the PCC transmission/reception device is mounted on avehicle, the PCC transmission/reception device may receive/processcontent data related to the AR/VR/PCC service according to a user inputsignal input through a user interface device and provide the same to theuser. The vehicle or the user interface device according to theembodiments may receive a user input signal. The user input signalaccording to the embodiments may include a signal indicating theself-driving service.

The point cloud data transmission method/device according to theembodiments is construed as a term referring to the transmission device10000 of FIG. 1 , the point cloud video encoder 10002 of FIG. 1 , thetransmitter 10003 of FIG. 1 , the acquisition 20000/encoding20001/transmission 20002 of FIG. 2 , the point cloud video encoder ofFIG. 4 , the transmission device of FIG. 12 , the device of FIG. 14 ,the transmission method of FIG. 42 , and the like.

The point cloud data reception method/device according to theembodiments is construed as a term referring to the reception device10004, the receiver 10005 of FIG. 1 , the point cloud video decoder10006 of FIG. 1 , the transmission 20002/decoding 20003/rendering 20004of FIG. 2 , the decoder of FIG. 10 , the point cloud video decoder ofFIG. 11 , the reception device of FIG. 13 , the device of FIG. 14 , thereception device of FIG. 43 , and the like.

The method/device for transmitting or receiving point cloud dataaccording to the embodiments may be referred to simply as amethod/device.

According to embodiments, geometry data, geometry information, andposition information constituting point cloud data are to be construedas having the same meaning. Attribute data, attribute information, andattribute information constituting the point cloud data are to beconstrued as having the same meaning.

The method/device according to the embodiments may process point clouddata in consideration of scalable transmission.

The method/device according to the embodiments may need selectivedecoding of a part of data due to receiver performance, the transmissionspeed, or the like in transmitting and receiving point cloud data. Inthis regard, a method for efficiently supporting the selective decodingis described.

To this end, in the present disclosure, geometry and attribute data maybe divided into units such as geometry octree and LoD (Level of Detail)to select information required in the bitstream level, or removeunnecessary information.

In addition, in the present disclosure, the geometry and attribute datamay be transmitted in multiple slices, such that the reception devicemay perform selective decoding or parallel decoding.

According to embodiments, a geometry bitstream and/or an attributebitstream, and/or a point cloud bitstream structure in which thegeometry bitstream and the attribute bitstream are multiplexed may besubdivided, and the subdivided bitstreams may be transmitted on aslice-by-slice basis. Thereby, the reception device may performselective decoding or parallel decoding.

In embodiments, a technique for constructing a data structure composedof a point cloud will be discussed. Specifically, a method for reducingperformance degradation that may occur due to segmentation inconfiguring slices and reducing a burden on the receiver is proposed.Referring to the point cloud data transmission/reception device (whichmay be referred to simply as an encoder/decoder) according to theembodiments shown in FIGS. 4 and 11 , point cloud data is composed of aset of points. Each of the points includes geometry information (orgeometry or geometry data) and attribute information (or an attribute orattribute data). The geometry information is three-dimensional positioninformation (xyz) about each point. That is, the position of each pointis represented by parameters in a coordinate system representing athree-dimensional space (e.g., parameters (x, y, z) of three axesrepresenting the space, such as the X-axis, Y-axis, and Z-axis). Theattribute information represents the color (RGB, YUV, etc.),reflectance, normal vectors, transparency, and the like of the points.In point cloud compression (PCC), octree-based compression is performedto efficiently compress non-uniform distribution in a three-dimensionalspace, and attribute information is compressed based on the octree-basedcompression. The point cloud video encoder and the point cloud videodecoder shown in FIGS. 4 and 11 may process operation(s) according toembodiments through respective components.

According to embodiments, the transmission device compresses thegeometry information (e.g., position) and attribute information (e.g.,color/brightness/reflectance, etc.) about the point cloud data andtransmits the compressed information to the reception device. In thiscase, point cloud data may be configured according to an octreestructure that has layers according to the degree of detail or levels ofdetail (LoDs). Then, scalable point cloud data coding and representationmay be performed based the configuration. In this case, only a part ofthe point cloud data may be decoded or represented according to theperformance of the reception device or the transfer rate.

That is, in the case where only a part of the scalable point cloudcompression bitstream needs to be transmitted (e.g., when only a part ofthe layers are decoded in scalable decoding), the necessary part cannotbe selected and sent. Accordingly, the transmission device is requiredto re-encode the necessary part after decoding as shown in FIG. 15 .Alternatively, after the entire data is delivered to the receptiondevice, the reception device is required to selectively apply thenecessary data after decoding.

However, in the case of FIG. 15 , a delay may occur due to the time fordecoding and re-encoding. Also, in the case of FIG. 16 , bandwidthefficiency may be degraded due to transmission of unnecessary data tothe reception device. Further, when a fixed bandwidth is used, dataquality may need to be lowered for transmission.

Accordingly, in order to address this issue, the method/device accordingto the embodiments may provide slices such that the point cloud may bedivided into regions and processed.

In particular, in the method/device according to the embodiments, slicesmay be divided and transmitted. When slices are independently coded,compression efficiency may be lowered due to deterioration of entropycontinuity. In this regard, in the method/device according to theembodiments, a method for continuously using entropy between separatedslices is proposed. In this regard, the resources of the receptiondevice may be efficiently managed by pre-transmitting information aboutthe slices that are continuously used. In addition, it may be necessaryto use information of another slice to refer to a neighbor at a boundaryof a separated slice. In this regard, proposed herein is a method ofprocessing at the slice boundary in order to guarantee independencebetween slices for parallel processing or to increase compressionefficiency. In the device and method according to the embodiments, amethod for efficiently performing buffer management by a receptiondevice when entropy continuity is given between multiple slices isproposed.

Also, in the method/device according to the embodiments, a slicesegmentation structure of point cloud data may be defined, and ascalable layer and slice structure for scalable transmission may besignaled.

In addition, according the present disclosure, geometry and attributedata may be transmitted through multiple slices. Thereby, the receptiondevice may perform selective decoding or parallel decoding.

According to embodiments, the method/device segments (or divides,separates, or partitions) a slice into multiple slices and transmit apoint cloud bitstream through the multiple segmented slices. Thereby,selective decoding or parallel decoding by the reception device may besupported.

In this regard, the present disclosure may define a brick as asuperordinate concept to the segmented slices. According to embodiments,a brick may be considered as a sub-tree for a tree constituting inputdata. In addition, each brick may be considered as a unit includingsub-tree depths of an occupied node at a specific tree depth withrespect to the tree structure constituting the input data.

FIG. 17 illustrates an example of configuring one or more bricks in atree structure according to embodiments.

Referring to FIG. 17 as an example, four sub-trees in which occupiednodes for a tree depth 2 are considered as roots are configured asdifferent bricks. For example, a tree structure based on point clouddata (e.g., geometry data) may be divided into four bricks indicated by50001, 50003, 50005, and 50007, respectively. The number of bricks shownin FIG. 17 is merely an exemplary embodiment for understanding of thoseskilled in the art. The number of bricks may vary. In addition, pointcloud data belonging to each brick may be transmitted through each dataunit. Here, each brick may be configured independently. In this case,parallel processing may be performed. Also, a brick may be composed ofone or more slices.

FIGS. 18A to 18C illustrate examples of a matching relationship betweentree layers and slices established to transmit point cloud databelonging to a brick according to embodiments.

When the transmission method/device/encoder according to the embodimentsdivides the point cloud bit stream in a slice structure, slices, whichare detailed units, may be configured. A data unit for detailed datarepresentation may be a slice.

For example, one or more octree layers may be matched to a slice.

The transmission method/device according to the embodiments, forexample, the encoder, may configure a slice 51001-based bitstream byscanning nodes (points) included in an octree in a scan order 51000direction. A slice may include nodes of one or more levels in the octreestructure, may include only nodes of a specific level, or may includeonly some nodes of a specific level. Alternatively, it may include onlysome nodes of one or more levels.

FIG. 18A shows an exemplary octree structure composed of 7 slices. Inthis example, a slice 51002 may include nodes of level 0 to level 4. Aslice 51003 may include some nodes of level 5, a slice 51004 may includesome nodes of level 5, and a slice 51005 may include some other nodes oflevel 5. That is, in FIG. 18A, level 5 is divided into three slices.Similarly, in FIG. 18A, level 6 (i.e., the leaf level) is also dividedinto three slices. In other words, a slice may be configured with somenodes of a specific level.

FIG. 18B shows an exemplary octree structure composed of four slices. Inthis example, a slice is composed of the nodes of level 0 to level 3 andsome nodes of level 4, and another slice is composed of the remainingnodes of level 4 and some nodes of level 5. In addition, another sliceis composed of the remaining nodes of level 5 and some nodes of level 6,and the other slice is composed of the remaining nodes of level 6.

FIG. 18C shows an exemplary octree structure composed of five slices. aslice is composed of the nodes of level 0 to level 3, and four slicesare composed of the nodes of level 4 to level 6. That is, a slice iscomposed of some nodes of level 4, some nodes of level 5, and some nodesof level 6.

In other words, as shown in FIGS. 18B and 18C, when multiple octreelayers are matched to a slice, only some nodes of each of the layers maybe included in the slice. When multiple slices constitute ageometry/attribute frame in this way, information necessary for thereception device to configure layers may be transmitted to the receptiondevice through signaling information. For example, the signalinginformation may include layer information included in each slice andnode information included in each layer. In FIGS. 18A to 18C, a hollowcircle (e.g., 51007) may serve to indicate a coding unit, and a solidcircle (e.g., 51008) may indicate the end point of the correspondingslice (or the start point of the previous slice).

The encoder and the device corresponding to the encoder according to theembodiments may encode the point cloud data, and generate and transmit abitstream including the encoded data and signaling information (orparameter information) about the point cloud data.

Furthermore, the bitstream may be generated based on the bitstreamstructure according to the embodiments. Accordingly, the receptiondevice, the decoder, a corresponding device, or the like according tothe embodiments may receive and parse a bitstream configured to besuitable for selective decoding of some data, thereby decoding only apart of the point cloud data and providing the same efficiently.

Next, scalable transmission of point cloud data will be described.

The point cloud data transmission method/device according to theembodiments may scalably transmit a bitstream including point clouddata, and the point cloud data reception method/device according to theembodiments may scalably receive the bitstream and decode the same.

When the structure illustrated FIGS. 18A to 18C is used for scalabletransmission, signaling information for selecting a slice required bythe reception device may be transmitted to the reception device. Thescalable transmission does not mean transmitting or decoding the entirebitstream, but means transmitting or decoding only a part of thebitstream. Accordingly, the reception device may provide low resolutionpoint cloud data (or content).

When the scalable transmission is applied to an octree-based geometrybitstream according to embodiments, point cloud data should be allowedto be constructed using only information up to a specific octree layerfor the bitstream of each octree layer from a root node to a leaf node.

To this end, a target octree layer should not have a dependency on loweroctree layer information. This may be a constraint applied togeometry/attribute coding in common.

In addition, in scalable transmission, the transmission/reception deviceneeds to transmit a scalable structure for selecting a scalable layer tothe reception device. Considering the octree structure according to theembodiments, all octree layers may support scalable transmission, orscalable transmission may be allowed only for a specific octree layer orlower layers. For example, some of the octree layers are included,signaling information may be delivered to the reception device toindicate a scalable layer in which a slice is included. Thus, thereception device may determine whether the slice isnecessary/unnecessary in the bitstream step. In the example of FIG. 18A,level 0 (i.e., root level) to level 4 51002 may constitute one scalablelayer without supporting scalable transmission, and the lower octreelayers may be matched to scalable layers in a one-to-one correspondencemanner. In general, scalability may be supported for a partcorresponding to the leaf node. As shown in FIG. 18C, when multipleoctree layers are included in a slice, it may be defined that onescalable layer shall be configured for the layers.

In this case, scalable transmission and scalable decoding may be usedseparately depending on the purpose. According to embodiments, thescalable transmission may be used in order for thetransmitting/reception device to select information up to a specificlayer without operation of the decoder. According to embodiments,scalable decoding may be used for the purpose of selecting a specificlayer during coding. That is, the scalable transmission may supportselection of necessary information without involving the decoder in acompressed state (i.e., in the bitstream stage), such that thetransmission or reception device may determine a specific layer. On theother hand, in the case of scalable decoding, encoding/decoding may besupported only up to a part required in the encoding/decoding process.Therefore, scalable decoding may be used in the case of scalablerepresentation.

In this case, the layer configuration for scalable transmission may bedifferent from the layer configuration for scalable decoding. Forexample, the lower three octree layers including leaf nodes mayconstitute one layer from the perspective of scalable transmission. Onthe other hand, from the perspective of scalable decoding, when alllayer information is included, scalable decoding may be possible foreach of the leaf node layers, leaf node layer-1 and leaf node layer-2.

The slice structure for layer configuration and the signaling method forscalable transmission described above will be described in more detaillater.

As described above, the method/device according to the embodiments maydivide and process the bitstream into specific units for efficientbitstream transmission and decoding.

The method/device according to the embodiments enables the point clouddata composed of layers to be selectively transmitted and decoded in thebitstream level.

The unit according to the embodiments may be referred to as an LOD, alayer, a slice, or the like. LOD is the same term as LOD in attributedata coding, but may mean a data unit for a layered structure of abitstream. The LOD according to the embodiments may be a conceptcorresponding to one depth or a bundle of two or more depths based onthe hierarchical structure of point cloud data, for example, depths(levels) of an octree or multiple trees. Similarly, a layer is providedto generate a unit of a sub-bitstream, and is a concept that correspondsto one depth or a bundle of two or more depths, and may correspond toone LOD or two or more LODs. Also, a slice is a unit for configuring aunit of a sub-bitstream, and may correspond to one depth, a part of onedepth, or two or more depths. Also, a slice may correspond to one LOD, apart of one LOD, or two or more LODs. According to embodiments, the LOD,the layer, and the slice may correspond to each other or one of the LOD,the layer, and the slice may be included in another one. Also, a unitaccording to embodiments may include an LOD, a layer, a slice, a layergroup, or a subgroup, and may be referred to as complementary to eachother. According to embodiments, in the octree structure, a layer, adepth, a level, and a depth level may have the same meaning.

FIG. 19 is a diagram illustrating an example of layer-basedconfiguration of point cloud data according to embodiments. FIG. 19shows an exemplary octree structure in which the depth level of the rootnode is set to 0 and the depth level of the leaf node is set to 7.

The transmission method/device according to the embodiments mayconfigure layer-based point cloud data as shown in FIG. 19 to encode anddecode the point cloud data.

Layering of point cloud data according to the embodiments may have alayer structure in terms of SNR, spatial resolution, color, temporalfrequency, bit depth, or the like depending on the application field,and may construct layers in a direction in which data density increasesbased on the octree structure or LOD structure.

That is, when the LOD is generated based on the octree structure, theymay be defined such that the LOD increases in a direction in which thedetail is increased, that is, in a direction in which the octree depthlevel is increased. In the present disclosure, a layer may have the samemeaning as a level, a depth, and a depth level.

Referring to FIG. 19 , for example, in an octree structure having 7depth levels except for the root node level (or referred to as a rootlevel), LOD 0 is configured to include levels from the root node levelto the octree depth level 4, and LOD 1 is configured to include levelsfrom the root node level to octree depth level 5, and LOD 2 isconfigured to include levels from root node level to octree depth level7.

According to embodiments, a bitstream acquired through point cloudcompression may be delivered by being divided into a geometry bitstreamand an attribute bitstream according to the type of data as shown inFIG. 20 . In this case, each bitstream may be configured as a slice andtransmitted.

FIG. 20 is a diagram illustrating an example in which a geometrybitstream and an attribute bitstream are included in respective slicesaccording to embodiments. That is, referring to FIG. 20 , a geometrybitstream including geometry data may be configured as slice0, and anattribute bitstream including attribute data may be configured asslice1.

The method/device according to the embodiments may generate LODs basedon the layering of the octree structure as shown in FIG. 19 andconfigure a geometry bitstream and an attribute bitstream as shown inFIG. 20 .

When the geometry bitstream and the attribute bitstream are configuredin one slice and delivered regardless of the layer information or LoDinformation, an operation of decoding the bitstream, an operation ofselecting only a desired part and removing unnecessary parts, and anoperation of re-encoding the bitstream based on only the necessaryinformation should be performed to use only a part of the layers orLoDs.

The present disclosure proposes a method of dividing a bitstream intomultiple slices and transmitting the bitstream in order to avoid suchunnecessary intermediate operations.

FIG. 21(a) is a diagram illustrating an example of dividing a geometrybitstream into multiple slices according to embodiments, and FIG. 21(b)is a diagram illustrating an example of dividing an attribute bitstreaminto multiple slices according to embodiments.

That is, when the bitstream is divided into multiple slices andtransmitted to the reception device, the geometry bitstream and theattribute bitstream may be divided into multiple slices and transmittedas shown in FIGS. 21(a) and 21(b). Each slice is composed of a sliceheader (also referred to as a data unit header) and slice data (alsoreferred to as data unit data). In this case, the slice header includesreference information related to the slice and/or a reference slice(e.g., a previous slice), and the slice data includes an actualbitstream.

In this case, each of the divided slices may be present independently.That is, in the example of FIGS. 21(a) and 21(b), geometry slices (slice0, slice 1, slice 2) may be coded without a correlation among slice 0,slice 1, and slice 2. In this case, since each slice may be codedindependently, three geometry coders may be operated simultaneously interms of parallel processing. Accordingly, slices may be mostefficiently configured based on the execution time in the applicationfield of live encoding/decoding and the like. For example, in the caseof predictive geometry coding in which the correlation between layers ispoor, slices may be configured independently of each other as shown inFIG. 21(a). In this case, the number of independently decodable slicesmay be indicated to the reception device through signaling information,thereby allowing the reception device to perform a parallel operation.This scheme may be equally or similarly applied to attribute slices(slice 3, slice 4, and slice 5).

As another method, when a bitstream is divided into multiple slices andtransmitted, the correlation between the slices may be considered asshown in FIGS. 22(a) and 22(b). FIG. 22(a) is a diagram illustratinganother example of dividing a geometry bitstream into multiple slicesaccording to embodiments, and FIG. 22(b) is a diagram illustratinganother example of dividing an attribute bitstream into multiple slicesaccording to embodiments.

For example, for octree-based geometry coding, compression performancemay be enhanced by sequentially and cumulatively using contextinformation about previous nodes. In addition, in neighbor search andintra prediction, decoded occupancy information about a neighbor (orperipheral) node is first used. In this case, information about theprevious slice may be used. Alternatively, the information about thepreceding slice may be used for parallel processing. In this case, asshown in FIGS. 22(a) and 22(b), dependency between slices occurs. Inthis case, information about the preceding slice may be specified bydelivering the same to the reception device through signalinginformation.

FIG. 22(a) illustrates an example in which slice 2 refers to slice 1 andslice 1 refers to slice 0. FIG. 22(b) illustrates an example in whichslice 5 refers to slice 4 and slice 4 refers to slice 3.

In this regard, various embodiments may be applied as a bitstreamsorting method for delivering a geometry bitstream and an attributebitstream through multiple slices.

FIG. 23 illustrates an exemplary method of sorting a geometry bitstreamand an attribute bitstream according to embodiments.

In transmitting a bitstream, the transmission method/device according tothe embodiments may transmit geometry data (or referred to as a geometrybitstream or geometry information) and attribute data (or referred to asan attribute bitstream or attribute information) in series as shown inFIG. 23 . In this operation, depending on the type of data, the entiregeometry data may be transmitted first, and then the attribute data maybe transmitted. In this case, the geometry data may be quicklyreconstructed based on the transmitted bitstream information.

FIG. 23 illustrates an example in which slice 0, slice 1, slice 2, whichcontain geometry data, slice 3, slice 4, and slice 5, which containattribute data, are transmitted in order. In this case, the positionsmay be changed according to embodiments. Also, reference may be madebetween geometry headers, and between an attribute header and a geometryheader.

FIG. 24 illustrates another exemplary method of sorting a geometrybitstream and an attribute bitstream according to embodiments.

In transmitting a bitstream, the transmission method/device according tothe embodiments may collect and transmit a geometry bitstream and anattribute bitstream constituting the same layer as shown in FIG. 24 . Inthis case, by using a compression technique capable of parallel decodingof geometry and attributes, the decoding execution time may beshortened. In this case, information that needs to be processed first(i.e., lower LoD, wherein geometry must precede attribute) may be placedfirst.

FIG. 24 illustrates an example in which slice 0 containing geometrydata, slice 3 containing attribute data, slice 1 containing geometrydata, slice 4 containing attribute data, slice 2 containing geometrydata, and slice 5 containing attribute data are transmitted in thisorder. In this case, the positions may be changed according toembodiments. Also, reference may be made between geometry headers, andbetween an attribute header and a geometry header.

The transmission/reception method/device according to the embodimentsmay efficiently select a desired layer (or LoD) in an application fieldat a bitstream level in transmitting and receiving a bitstream. In thebitstream sorting method according to the embodiments, collecting andtransmitting geometry information as shown in FIG. 23 may produce anempty part in the middle after a specific bitstream level is selected.In this case, the bitstream may need to be rearranged.

By bundling and transmitting the geometry data and attribute dataaccording to layers as shown in FIG. 24 , necessary information may beselectively delivered and/or unnecessary information may be selectivelyremoved according to an application field.

For example, referring to FIG. 24 , when a part of the bitstream needsto be selected, the transmission device may select and transmit onlygeometry slice 0 and attribute slice 3 of one layer, and geometry slice1 and attribute slice 4 of another layer and remove geometry slice 2 andattribute slice 5 of another layer from the bitstream. That is, in thecase of symmetrical geometry-attribute selection, geometry data andattribute data of the same layer are simultaneously selected andtransmitted, or simultaneously selected and removed.

For example, referring to FIG. 24 , when a part of the bitstream needsto be selected, the transmission device may select and transmit geometryslice 0 and attribute slice 3 of one layer, geometry slice 1 andattribute slice 4 of another layer, and geometry slice 2 betweengeometry slice 2 and attribute slice 5 of another layer, and removeattribute slice 5 from the bitstream. That is, in the case of asymmetricgeometry-attribute selection, only one of the geometry data and theattribute data of the same layer is selected and transmitted or removed.

Segmentation of the bitstream and selection of a part of the bitstreamdescribed above are intended to support the scalability of the pointcloud data.

Hereinafter, a continuous slice operation and management of a contextbuffer will be described. According to an embodiment, the context buffermay include a geometry buffer and/or an attribute buffer of thereception device of FIG. 43 .

As described above, in octree-based geometry coding, compressionperformance may be increased by sequentially and cumulatively usingcontext information about previous nodes. In addition, in neighborsearch and intra prediction, decoded occupancy information about aneighbor (or peripheral) node is first used. In this case, informationabout the previous slice may be used. Alternatively, the informationabout the preceding slice may be used for parallel processing. In thiscase, dependency between slices occurs.

In the case of a dependent slice, by using the information about theprevious slice for coding of the subsequent slice, degradation of codingefficiency caused by dividing the slice may be addressed. In geometrycoding, information such as context-based adaptive binary arithmeticcoding (CABAC) context, a context map, dictionary LuT, and planar codingvariables may be used continuously. When the context is continuouslyused in this way, it is necessary to control the context buffer.

FIG. 25A is a diagram illustrating an example of dependency betweenslices in a bitstream structure according to embodiments. FIG. 25B is adiagram illustrating an example of contexts generated in respectiveslices when inter-slice dependency occurs as shown in FIG. 25A. FIGS.25C to 25E are diagrams illustrating examples of context buffer controlwhen inter-slice dependency occurs according to embodiments.

FIG. 25A illustrates an example in which a bitstream is divided intomultiple slices and transmitted, and thus slice 2 and slice 3 useinformation of slice 0, and slice 4 uses information of slice 3. Thatis, slice 2 and slice 3 depend on slice 0, and slice 4 depends on slice3. For example, since encoding of slice 2 is performed based on contextinformation (e.g., geometry data or attribute data) of slice 0, encodingof slice 2 may start after encoding of slice 0 is completed. In FIG.25A, slice 0 is referenced by slice 2 and slice 3, and accordingly thenumber of times slice 0 is referenced by other slices may be 2. Incontrast, slice 1 is independent of other slices. Therefore, data (e.g.,geometry data or attribute data) of slice 1 may be independently encodedwithout a relation to other slices.

Although the embodiment of FIG. 25A is described in consideration of acase where the tree is divided into slices, this is merely an example.That is, continuation information, context usage information, andneighbor reference status about another brick, another tile, or anotherframe may be used even for a bitstream divided into bricks, which are aconcept including a subtree, or tiles or frames, which are divided byregions.

When data (e.g., geometry data or attribute data) belonging to eachslice are encoded by the encoder, a context is generated for each slice.Here, the encoder may be the point cloud video encoder 10002 of FIG. 1 ,the encoding 20001 of FIG. 2 , the point cloud video encoder of FIG. 4 ,the transmission device of FIG. 12 , the encoder of FIG. 42 , or thelike.

Referring to FIG. 25B, when data of a first slice (slice 0) is input tothe encoder, context A, which is context information, is generated byencoding. Then, when data of a second slice (slice 1) is encoded by theencoder, context B is generated. When data of a third slice (slice 2) isencoded by the encoder, context A′ is generated. In addition, context A″is generated when data of a fourth slice (slice 3) is encoded by theencoder, and context C is generated when data of a fifth slice (slice 4)is encoded by the encoder. For example, context A′ refers to contextAbut is independent (or different) from context A. That is, context A′is the context configured by updating context A.

Then, the reception device stores the context of each slice in thecontext buffer.

At this time, when all contexts are stored in the context buffer withoutcontrol of the context buffer as shown in FIG. 25C, the storage spacemay become insufficient or the cost may increase to secure a largerstorage space.

Therefore, the present disclosure proposes a method to efficientlycontrol the context buffer. FIGS. 25D and 25E are diagrams illustratingexamples of context buffer control according to embodiments.

Referring to FIG. 25D, when data of the first slice (slice 0) is inputto the encoder of the transmission device, context A, which is contextinformation, is generated by encoding. Since context A is used by one ormore subsequent slices (e.g., slice 2, slice 3, and other slices notshown), context A is stored in the context buffer in the receptiondevice. In this case, the transmission device may transmit informationabout slices (e.g., slice 2 and slice 3) that use the context of slice 0to the reception device through signaling information (e.g., buffercontrol related information). Accordingly, the reception device mayefficiently control the buffer (or context buffer). For example, thetotal number of slices (=N) (e.g., num_context_reuse_minus1) that usecontext A among the subsequent slices may be transmitted to thereception device through signaling information (e.g., buffer controlrelated information or counter). For example, in the case of FIG. 25A, Nmay be 3. For N greater than 0, when context A is referenced N times byother slices after context A is stored in the context buffer of thereception device, context A may be removed from the context buffer. InFIG. 25D, “in” means storing the context in the context buffer, and‘out’ means removing the context from the context buffer.

According to embodiments, since slice 0 is used by slice 2, slice 3, andother slices not shown, context A, which is the context of slice 0, isnot removed from the context buffer, but is kept stored (context A(in)).

According to embodiments, slice 1 is independently coded (or decoded)without a relation to slice 0 and subsequent slices, and thereforecontext B, which is the context of slice 2, may be removed from thecontext buffer immediately after being processed (context B(in/out)).According to embodiments, when slice 0 is processed, slice 1 may beprocessed in parallel at the same time. Thereby, the execution time maybe shortened.

According to embodiments, slice 2 refers to slice 0, but has no relationto subsequent slices. Accordingly, context A′, which is the context ofslice 2, may be removed immediately after being processed in the contextbuffer (context A′(in/out)). Since coding (or decoding) of slice 2 isperformed based on context A, which is the context (or contextinformation) of slice 0, coding (or decoding) of slice 0 may start aftercoding (or decoding) of slice 0 is completed. Since slice 2 is notreferenced by a subsequent slice, it may be deleted from the contextbuffer after coding (or decoding) thereof is completed.

According to embodiments, since slice 3 is used in slice 4 and otherslices not shown, context A″, which is the context of slice 3, is notremoved from the context buffer, but is kept stored (context A″(in)).Similarly to slice 2, coding (or decoding) of slice 3 is performed basedon context A of slice 0. Accordingly, coding (or decoding) of slice 3may be performed in parallel with coding (or decoding) of slice 2 at thesame time. Thereby, the execution time may be shortened. However, thecontext generated in slice 3 (that is, context A″) is not removed afterbeing stored in the context buffer because it is used for coding (ordecoding) of a subsequent slice. The context A″ stored in the contextbuffer is used for coding (or decoding) of slice 4.

According to embodiments, slice 4 refers to slice 3, but has no relationto subsequent slices. Accordingly, context C, which is the context ofslice 4, may be removed immediately after being processed in the contextbuffer (context C(in/out)).

According to embodiments, the period during which the context generatedafter encoding of a specific slice is stored in the context buffer maybe determined based on the number of times the slice is referenced by atleast one subsequent slice.

When there is additional information about the context buffer asdescribed above, the context buffer may be efficiently managed byremoving the context from the context buffer when the context is nolonger used based on information about whether the context isadditionally used and how many times the context is additional used..That is, the context of a slice that has no relation to subsequentslices may be removed immediately after being processed in the contextbuffer. Thereby, the context buffer may be efficiently controlled. Inaddition, when parallel processing can be performed based on dependencyinformation, the execution time may be shortened through simultaneousexecution.

25(e) shows an example of context buffer control performed when two ormore slices are processed in parallel.

For example, when slice 0 and slice 1 are processed in parallel, contextA of slice 0 and context B of slice 1 are stored in the context buffersimultaneously. In this regard, since slice 0 is used by slice 2, slice3, and other slices not shown, context A is not removed from the contextbuffer, but is kept stored (context A(in)). However, slice 1 has norelation to slice 0 and subsequent slices, and therefore context B isremoved from the context buffer immediately after being processed(context B(in/out)).

As another example, when slice 2 and slice 3 are processed in parallel,context A′ of slice 2 and context A″ of slice 3 are stored in thecontext buffer simultaneously. Since slice 2 is not used in subsequentslices, context A′ is removed immediately after being processed in thecontext buffer (context A′(in/out)). However, slice 3 is used in slice4, and therefore context A″ is not removed from the context buffer, butis kept stored (context A″(in)).

Hereinafter, a continuous slice operation (neighbor continuation) willbe described.

According to embodiments, when coding is performed by dividing slices,positionally adjacent nodes may be present in different slices.

FIGS. 26A to 26D are diagrams illustrating examples of a neighborstructure according to embodiments.

As an example, in the neighbor structure of FIGS. 26A to 26D, a node53000 positioned at the center is present at the boundary of a slice,nodes 1, 8, and 32 may be present in the same slice, but nodes 2, 4 and16 may be present in one or more different slices. In this case,considering the relation with neighbor (or peripheral) nodes, theneighbor nodes may or may not be used depending on whether thedependency between slices. For example, when neighbor nodes are used,the dependency between slices and a slice including each neighbor nodemay be signaled. FIGS. 26A to 26D show examples of 6 dependent neighbornodes, 18 dependent neighbor nodes, and 32 dependent neighbor nodesalong with a node positioned at the center. When the dependency is notacknowledged, neighbor search may be used on the assumption that thereis no corresponding neighbor node, that all neighbor nodes are occupied,or that the neighbor nodes are non-occupied (that is, unoccupied). Whensuch assumption is used, relevant information may be transmitted to thereception device through signaling information. In this case, there maybe a possibility of parallel processing in the sense that each slice maybe processed independently. Conversely, when the information about theneighbor node is used accurately, the result of processing of theneighbor slice may be required. Such relation to neighbor nodes may beused in operations such as obtaining an occupancy map of geometrycoding, neighbor search of LoD generation, and prediction of RAHT.

While FIGS. 26A to 26D are described in consideration of a case where atree is divided into slices, continuation information, context usageinformation, and a neighbor reference status may be used even for abitstream divided into bricks, which are a concept including a subtree,or tiles or frames, which are divided by regions.

FIG. 27 is a diagram illustrating an example of a bitstream structure ofpoint cloud data for transmission/reception according to embodiments.According to embodiments, the bitstream output from the point cloudvideo encoder of any one of FIGS. 1, 2, 4, 12, and 42 may take the formof FIG. 27 .

According to embodiments, the bitstream of the point cloud data providestiles or slices such that the point cloud data may be divided intoregions and processed. The regions of the bitstream may have differentimportance levels. Accordingly, when the point cloud data is partitionedinto tiles, different filters (encoding methods) or different filterunits may be applied to the respective tiles. When the point cloud datais partitioned into slices, different filters or different filter unitsmay be applied to the respective slices.

When the point cloud data is partitioned into regions and compressed,the transmission device and the reception device according to theembodiments may transmit and receive a bitstream in a high-level syntaxstructure for selective transmission of attribute information in thepartitioned regions.

The transmission device according to the embodiments may transmit pointcloud data according to the bitstream structure as shown in FIG. 27 .Accordingly, a method to apply different encoding operations and use agood-quality encoding method for an important region may be provided. Inaddition, efficient encoding and transmission may be supported accordingto the characteristics of point cloud data, and attribute values may beprovided according to user requirements.

The reception device according to the embodiments may receive the pointcloud data according to the bitstream structure as shown in FIG. 27 .Accordingly, different filtering (decoding) methods may be applied tothe respective regions (tiles or regions partitioned into slices),rather than a complexly decoding (filtering) method being applied to theentire point cloud data. Therefore, better image quality in a regionimportant to the user and an appropriate latency to the system may beensured.

When a geometry bitstream, an attribute bitstream, and/or a signalingbitstream (or signaling information) according to embodiments areconfigured in one bitstream (or G-PCC bitstream) as shown in FIG. 27 ,the bitstream may include one or more sub-bitstreams. The bitstreamaccording to the embodiments may include a sequence parameter set (SPS)for sequence-level signaling, a geometry parameter set (GPS) forsignaling of geometry information coding, and one or more attributeparameter sets (APSs) APS₀ and APS₁ for signaling of attributeinformation coding, a tile inventory (or referred to as TPS) fortile-level signaling, and one or more slices (slice 0 to slice n). Thatis, the bitstream of point cloud data according to the embodiments mayinclude one or more tiles. Each tile may be a slice group including oneor more slices (slice 0 to slice n). The tile inventory (i.e., TPS)according to the embodiments may include information about each of oneor more tiles (e.g., coordinate value information and height/sizeinformation about a tile bounding box). Each slice may include onegeometry bitstream (Geom0) and/or one or more attribute bitstreams(Attr0, Attr1). For example, slice 0 may include one geometry bitstreamGeom0⁰ and one or more attribute bitstreams Attr0⁰ and Attr1⁰.

The geometry bitstream in each slice may be composed of a geometry sliceheader (geom_slice_header) and geometry slice data (geom_slice_data).According to embodiments, the geometry bitstream in each slice may bereferred to as a geometry data unit, the geometry slice header may bereferred to as a geometry data unit header, and the geometry slice datamay be referred to as geometry data unit data.

The attribute bitstream in each slice may be composed of an attributeslice header (attr_slice_header) and attribute slice data(attr_slice_data). According to embodiments, the attribute bitstream ineach slice may be referred to as an attribute data unit, the attributeslice header may be referred to as an attribute data unit header, andthe attribute slice data may be referred to as attribute data unit data.

According to embodiments, parameters required for encoding and/ordecoding of point cloud data may be newly defined in parameter sets(e.g., SPS, GPS, APS, and TPS (or referred to as a tile inventory),etc.) of the point cloud data and/or the header of the correspondingslice. For example, they may be added to the GPS in encoding and/ordecoding of geometry information, and may be added to the tile (TPS)and/or slice header in tile-based encoding and/or decoding.

According to embodiments, information related to slice (referred to asslice related information) and/or information related to buffer control(referred to as buffer control related information) may be signaled inat least one of the SPS, the GPS, the APS, the TPS, or an SEI message.Also, the information related to slice (referred to as slice relatedinformation) and/or the information related to buffer control (referredto as buffer control related information) may be signaled in at leastone of the geometry slice header (referred to as a geometry data unitheader) or the attribute slice header (referred to as an attribute dataunit header).

According to embodiments, the slice related information and/or thebuffer control related information may be defined in a correspondingposition or a separate position depending on an application or systemsuch that the range and method to be applied may be used differently. Afield, which is a term used in syntaxes that will be described later inthe present disclosure, may have the same meaning as a parameter or asyntax element.

That is, the signal (e.g., the slice related information and/or thebuffer control related information) may have different meaningsdepending on the position where the signal is transmitted. When thesignal is defined in the SPS, it may be equally applied to the entiresequence. When the signal is defined in the GPS, this may indicate thatthe signal is used for position reconstruction. When the signal isdefined in the APS, this may indicate that the signal is applied toattribute reconstruction. When the signal is defined in the TPS, thismay indicate that the signaling is applied only to points within a tile.When the signal is delivered in a slice, this may indicate that thesignaling is applied only to the slice. In addition, when the fields (orreferred to as syntax elements) are applicable to multiple point clouddata streams as well as the current point cloud data stream, they may becarried in a superordinate parameter set.

According to embodiments, parameters (which may be referred to asmetadata, signaling information, or the like) may be generated by themetadata processor (or metadata generator), signaling processor, orprocessor of the transmission device, and may be transmitted to thereception device and used in the decoding/reconstruction operation. Forexample, the parameters generated and transmitted by the transmissiondevice may be acquired by the metadata parser of the reception device.

In this embodiment, it has been described that information is definedindependently of the coding technique. However, in other embodiments,the information may be defined in connection with the coding technique.In order to support regionally different scalability, the informationmay be defined in the tile parameter set.

Alternatively, a network abstract layer (NAL) unit may be defined andrelevant information (e.g., the slice related information and/or thebuffer control related information) for selecting a layer, such as layerid, may be delivered. Thereby, a bitstream may be selected even at asystem level.

FIG. 28 shows an embodiment of a syntax structure of a sequenceparameter set (SPS) (seq_parameter_set( )) according to the presentdisclosure. The SPS may contain sequence information about a point clouddata bitstream.

The SPS according to the embodiments may include amain_profile_compatibility_flag field, aunique_point_positions_constraint_flag field, a level_idc field, ansps_seq_parameter_set_id field, an sps_bounding_box_present_flag field,an sps_source_scale_factor field, an numerator_minus1 field, ansource_scale_factor_denominator_minus1 field, an sps_num_attribute_setsfield, an log2_max_frame_idx field, an axis_coding_order field, ansps_bypass_stream_enabled_flag field, and an sps_extension_flag field.

The main_profile_compatibility_flag field may indicate whether thebitstream conforms to a main profile. For example, themain_profile_compatibility_flag field equal to 1 may indicate that thebitstream conforms to the main profile. For another example, themain_profile_compatibility_flag field equal to 0 may indicate that thebitstream conforms to a profile other than the main profile.

When the value of the unique_point_positions_constraint_flag field is 1,all output points may have unique positions in each point cloud framereferred to by the current SPS. When the value of theunique_point_positions_constraint_flag field is 0, two or more outputpoints may have the same position in a point cloud frame referred to bythe current SPS. For example, even though all points are unique in eachslice, slices and other points within a frame may overlap. In this case,the unique_point_positions_constraint_flag field is set to 0.

The level_idc field indicates a level to which the bitstream conforms.

The sps_seq_parameter_set_id field provides an identifier for the SPSfor reference by other syntax elements.

The sps_bounding_box_present_flag field may indicate whether a boundingbox is present in the SPS. For example, thesps_bounding_box_present_flag field equal to 1 indicates that a boundingbox is present in the SPS and the sps_bounding_box_present_flag fieldequal to 0 indicates that the size of the bounding box is undefined.

When the sps_bounding_box_present_flag field is equal to 1, the SPSaccording to embodiments may further include ansps_bounding_box_offset_x field, an sps_bounding_box_offset_y field, ansps_bounding_box_offset_z field, an sps_bounding_box_offset_log2_scalefield, an sps_bounding_box_size_width field, ansps_bounding_box_size_height field, and an sps_bounding_box_size_depthfield.

The sps_bounding_box_offset_x field indicates the x offset of the sourcebounding box in the Cartesian coordinates. When the x offset of thesource bounding box is not present, the value ofsps_bounding_box_offset_x is 0.

The sps_bounding_box_offset_y field indicates the y offset of the sourcebounding box in the Cartesian coordinates. When the y offset of thesource bounding box is not present, the value ofsps_bounding_box_offset_y is 0.

The sps_bounding_box_offset_z field indicates the z offset of the sourcebounding box in the Cartesian coordinates. When the z offset of thesource bounding box is not present, the value ofsps_bounding_box_offset_z is 0.

The sps_bounding_box_offset_log2_scale field indicates a scale factor toscale the quantized x, y, and z source bounding box offsets.

The sps_bounding_box_size_width field indicates the width of the sourcebounding box in the Cartesian coordinates. When the width of the sourcebounding box is not present, the value of thesps_bounding_box_size_width field may be 1.

The sps_bounding_box_size_height field indicates the height of thesource bounding box in the Cartesian coordinates. When the height of thesource bounding box is not present, the value of thesps_bounding_box_size_height field may be 1.

The sps_bounding_box_size_depth field indicates the depth of the sourcebounding box in the Cartesian coordinates. When the depth of the sourcebounding box is not present, the value of thesps_bounding_box_size_depth field may be 1.

The sps_source_scale_factor_numerator_minus1 field plus 1 indicates thescale factor numerator of the source point cloud.

The sps_source_scale_factor_denominator_minus1 field plus 1 indicatesthe scale factor denominator of the source point cloud.

The sps_num_attribute_sets field indicates the number of codedattributes in the bitstream.

The SPS according to embodiments includes an iteration statementrepeated as many times as the value of the sps_num_attribute_sets field.In an embodiment, i is initialized to 0, and is incremented by 1 eachtime the iteration statement is executed. The iteration statement isrepeated until the value of i becomes equal to the value of thesps_num_attribute_sets field. The iteration statement may include anattribute_dimension_minus1 [i] field and an attribute_instance_id[i]field. The attribute_dimension_minus1 [i] field plus 1 specifies thenumber of components of the i-th attribute.

The attribute_instance_id[i] field specifies an instance ID of the i-thattribute.

According to embodiments, when a value of attribute_dimension_minus1 [i]field is greater than 1, the iteration statement may further include anattribute_secondary_bitdepth_minus [i] field, anattribute_cicp_colour_primaries[i] field, anattribute_cicp_transfer_characteristics[i] field, anattribute_cicp_matrix_coeffs[i] field, anattribute_cicp_video_full_range_flag[i] field, and aknown_attribute_label_flag[i] field.

The attribute_secondary_bitdepth_minus [i] plus 1 specifies a bitdepthfor a second component of the i-th attribute signal(s).

The attribute_cicp_colour_primaries[i] field indicates chromaticitycoordinates of the color attribute source primaries of the i-thattribute.

The attribute_cicp_transfer_characteristics[i] field either indicatesthe reference opto-electronic transfer characteristic function of thecolour attribute as a function of a source input linear opticalintensity with a nominal real-valued range of 0 to 1 or indicates theinverse of the reference electro-optical transfer characteristicfunction as a function of an output linear optical intensity.

The attribute_cicp_matrix_coeffs[i] field describes the matrixcoefficients used in deriving luma and chroma signals from the green,blue, and red, or Y, Z, and X primaries.

The attribute_cicp_video_full_range_flag[i] field indicates the blacklevel and range of the luma and chroma signals as derived from E′Y,E′PB, and E′PR or E′R, E′G, and E′B real-valued component signals.

The known_attribute_label_flag[i] field specifies whether aknow_attribute_label[i] field or an attribute_label_four_bytes[i] fieldis signaled for the i-th attribute. For example, the value of theknown_attribute_label_flag[i] field equal to 0 specifies that theknown_attribute_label field is signaled for the ith attribute. Theknown_attribute_label_flag[i] field equal to 1 specifies that theattribute_label_four_bytes[i] field is signaled for the ith attribute.

The known_attribute_label[i] field indicates the type of the i-thattribute. For example, when the value of the known_attribute_label[i]field is 0, it may indicate that the i-th attribute is color. When thevalue of the known_attribute_label[i] field is 1, it may indicate thatthe i-th attribute is reflectance. When the value of theknown_attribute_label[i] field is 2, it may indicate that the i-thattribute is frame index. In addition, when the value of theknown_attribute_label[i] field is 4, it indicates that the i-thattribute is transparency. When the value of theknown_attribute_label[i] field is 5, it indicates that the i-thattribute is normals.

The attribute_label_four_bytes[i] field indicates a known attribute typein a 4-byte code.

According to embodiments, when the value of theattribute_label_four_bytes[i] is 0, it may indicate that the i-thattribute is color. When the value of the attribute_label_four_bytes[i]field is 1, it may indicate that the i-th attribute is reflectance. Whenthe value of the attribute_label_four_bytes[i] field is 2, it mayindicate that the i-th attribute is frame index. When the value of theattribute_label_four_bytes[i] field is 4, it may indicate that the i-thattribute is transparency. When the value of theattribute_label_four_bytes[i] field is 5, it may indicate that the i-thattribute is normals.

The log2_max_frame_idx field specifies the number of bits used to signala frame_idx syntax variable.

The axis_coding_order field i specifies the correspondence between theX, Y, and Z output axis labels and the three position components in thereconstructed point cloud RecPic [pointidx] [axis] with axis=0, . . . ,2.

The sps_bypass_stream_enabled_flag field equal to 1 may specify that thebypass coding mode is used on reading the bitstream. As another example,the sps_bypass_stream_enabled_flag field equal to 0 may specify that thebypass coding mode is not used on reading the bitstream.

The sps_extension_flag field indicates whether the sps_extension_datasyntax structure is present in the corresponding SPS syntax structure.For example, when the sps_extension_present_flag field is equal to 1, itindicates that the sps_extension_data syntax structure is present in theSPS syntax structure. When the sps_extension_present_flag field is equalto 0, it indicates that the sps_extension_data syntax structure is notpresent in the SPS syntax structure.

According to embodiments, when the sps_extension_flag field is equal to1, the SPS may further include a sps_extension_data_flag field.

The sps_extension_data_flag field may have any value.

FIG. 29 shows another embodiment of a syntax structure of an SPS(sequency_parameter_set( )) according to embodiments.

The SPS of FIG. 29 may further include a fieldsps_entropy_continuation_enabled_flag. For example,sps_entropy_continuation_enabled_flag equal to 1 indicates that aslice's initial entropy context state may depend upon the final entropycontext state of the preceeding slice.sps_entropy_continuation_enabled_flag equal to 0 specifies that theinitial entropy context state of each slice is independent.

According to embodiments, the fieldsps_entropy_continuation_enabled_flag of FIG. 29 may be included anyposition in the SPS of FIG. 28 .

FIG. 30 shows an embodiment of a syntax structure of the geometryparameter set (GPS) (geometry_parameter_set( )) according to the presentdisclosure. The GPS according to the embodiments may contain informationon a method of encoding geometry information about point cloud datacontained in one or more slices.

According to embodiments, the GPS may include agps_geom_parameter_set_id field, a gps_seq_parameter_set_id field, agps_box_present_flag field, a unique_geometry_points_flag field, ageometry_planar_mode_flag field, a geometry_angular_mode_flag field, aneighbour_context_restriction_flag field, aninferred_direct_coding_mode_enabled_flag field, abitwise_occupancy_coding_flag field, anadjacent_child_contextualization_enabled_flag field, alog2_neighbour_avail_boundary field, a log2_intra_pred_max_node_sizefield, a log2_trisoup_node_size field, a geom_scaling_enabled_flagfield, a gps_implicit_geom_partition_flag field, and agps_extension_flag field.

The gps_geom_parameter_set_id field provides an identifier for the GPSfor reference by other syntax elements.

The gps_seq_parameter_set_id field specifies the value ofsps_seq_parameter_set_id for the active SPS.

The gps_box_present_flag field specifies whether additional bounding boxinformation is provided in a geometry slice header that references thecurrent GPS. For example, the gps_box_present_flag field equal to 1 mayspecify that additional bounding box information is provided in ageometry header that references the current GPS. Accordingly, when thegps_box_present_flag field is equal to 1, the GPS may further include agps_gsh_box_log2_scale_present_flag field.

The gps_gsh_box_log2_scale_present_flag field specifies whether thegps_gsh_box_log2_scale field is signaled in each geometry slice headerthat references the current GPS. For example, thegps_gsh_box_log2_scale_present_flag field equal to 1 may specify thatthe gps_gsh_box_log2_scale field is signaled in each geometry sliceheader that references the current GPS. As another example, thegps_gsh_box_log2_scale_present_flag field equal to 0 may specify thatthe gps_gsh_box_log2_scale field is not signaled in each geometry sliceheader and a common scale for all slices is signaled in thegps_gsh_box_log2_scale field of the current GPS.

When the gps_gsh_box_log2_scale_present_flag field is equal to 0, theGPS may further include a gps_gsh_box_log2_scale field.

The gps_gsh_box_log2_scale field indicates the common scale factor ofthe bounding box origin for all slices that refer to the current GPS.

The unique_geometry_points_flag field indicates whether, in all slicesthat refer to the current GPS, all output points have unique positionswithin a slice. For example, the unique_geometry_points_flag field equalto 1 indicates that in all slices that refer to the current GPS, alloutput points have unique positions within a slice. Theunique_geometry_points_flag field equal to 0 indicates that in allslices that refer to the current GPS, the two or more of the outputpoints may have the same position within a slice.

The geometry_planar_mode_flag field indicates whether the planar codingmode is activated. For example, the geometry_planar_mode_flag fieldequal to 1 indicates that the planar coding mode is activated. Thegeometry_planar_mode_flag equal to 0 indicates that the planar codingmode is not activated.

When the geometry_planar_mode_flag field is equal to 1, that is, TRUE,the GPS may further include a geom_planar_mode_th_idcm field, ageom_planar_mode_th[1] field, and a geom_planar_mode_th[2] field.

The geom_planar_mode_th_idcm field may specify a value of a threshold ofactivation for the direct coding mode.

The geom_planar_mode_th[i] field specifies, for i in the range 0 . . .2, the value of the threshold of activation for the planar coding modealong the i-th most probable direction for the planar coding mode to beefficient.

The geometry_angular_mode_flag field indicates whether the angularcoding mode is active. For example, when the geometry_angular_mode_flagfield is equal to 1, it may indicate that the angular coding mode isactive. When the geometry_angular_mode_flag field is equal to 0, it mayindicate that the angular coding mode is not active.

When the value of the geometry_angular_mode_flag field is 1, that is,TRUE, the GPS may further include a lidar_head_position[0] field, alidar_head_position[1] field, a lidar_head_position[2] field, anumber_lasers field, a planar_buffer_disabled field, aimplicit_qtbt_angular_max_node_min_dim_log2_to_split_z field, and animplicit_qtbt_angular_max_diff_to_split_z field.

The lidar_head_position[0] field, the lidar_head_position[1] field, andthe lidar_head_position[2] field may represent (X, Y, Z) coordinates ofthe lidar head in a coordinate system with the internal axes.

The number_lasers field indicates the number of lasers used for theangular coding mode.

According to embodiments, the GPS includes an iteration statementiterated as many times as the value of the number_lasers field. In thiscase, according to an embodiment, i is initialized to 0, and isincremented by 1 each time the iteration statement is executed. Theiteration statement is iterated until the value of i becomes equal tothe value of the number_lasers field. This iteration statement mayinclude a laser_angle[i] field and a laser_correction[i] field.

The laser_angle[i] field indicates the tangent of the elevation angle ofthe i-th laser relative to the horizontal plane defined by the 0-th andfirst internal axes.

The laser_correction[i] field indicates correction of the i-th laserposition related to the lidar_head_position[2] field along the secondinternal axis.

When the planar_buffer_disabled field is equal to 1, it indicates thattracking the closest nodes using a buffer is not used in the process ofcoding the planar mode flag field and the plane position in the planarmode. When the planar_buffer_disabled field is equal to 0, it indicatesthat tracking the closest nodes using a buffer is used.

The implicit_qtbt_angular_max_node_min_dim_log2_to_split_z fieldindicates a log 2 value of a node size below which horizontal split ofnodes is preferred to vertical split.

The implicit_qtbt_angular_max_diff_to_split_z field indicates the log 2value of the maximum vertical over horizontal node size ratio allowedfor a node.

The neighbour_context_restriction_flag field equal to 0 indicates thatgeometry node occupancy of the current node is coded with the contextsdetermined from neighboring nodes which are located inside the parentnode of the current node. The neighbour_context_restriction_flag fieldequal to 1 indicates that geometry node occupancy of the current node iscoded with the contexts determined from neighboring nodes which arelocated inside or outside the parent node of the current node.

The inferred_direct_coding_mode_enabled_flag field indicates whether thedirect_mode_flag field is present in the geometry node syntax. Forexample, the inferred_direct_coding_mode_enabled_flag field equal to 1indicates that the direct_mode_flag field may be present in the geometrynode syntax. For example, the inferred_direct_coding_mode_enabled_flagfield equal to 0 indicates that the direct_mode_flag field is notpresent in the geometry node syntax.

The bitwise_occupancy_coding_flag field indicates whether geometry nodeoccupancy is encoded using bitwise contextualization of the syntaxelement occupancy map. For example, the bitwise_occupancy_coding_flagfield equal to 1 indicates that geometry node occupancy is encoded usingbitwise contextualisation of the syntax element occupancy map. Forexample, the bitwise_occupancy_coding_flag field equal to 0 indicatesthat geometry node occupancy is encoded using the dictionary encodedsyntax element occupancy byte.

The adjacent_child_contextualization_enabled_flag field indicateswhether the adjacent children of neighboring octree nodes are used forbitwise occupancy contextualization. For example, theadjacent_child_contextualization_enabled_flag field equal to 1 indicatesthat the adjacent children of neighboring octree nodes are used forbitwise occupancy contextualization. For example, the adjacentchild_contextualization_enabled_flag field equal to 0 indicates that thechildren of neighbouring octree nodes are not used for the occupancycontextualization.

The log2_neighbour_avail_boundary field specifies the value of thevariable NeighbAvailBoundary that is used in the decoding process. Forexample, when the neighbour_context_restriction_flag field is equal to1, NeighbAvailabilityMask may be set equal to 1. For example, when theneighbour_context_restriction_flag field is equal to 0,NeighbAvailabilityMask may be set equal to1<<log2_neighbour_avail_boundary.

The log2_intra_pred_max_node_size field specifies the octree node sizeeligible for occupancy intra prediction.

The log2_trisoup_node_size field specifies the variable TrisoupNodeSizeas the size of the triangle nodes.

The geom_scaling_enabled_flag field indicates whether a scaling processfor geometry positions is invoked during the geometry slice decodingprocess. For example, the geom_scaling_enabled_flag field equal to 1specifies that a scaling process for geometry positions is invokedduring the geometry slice decoding process. Thegeom_scaling_enabled_flag field equal to 0 specifies that geometrypositions do not require scaling.

The geom_base_qp field specifies the base value of the geometry positionquantization parameter.

The gps_implicit_geom_partition_flag field specifies whether theimplicit geometry partition is enabled for the sequence or slice. Forexample, the gps_implicit_geom_partition_flag field equal to 1 specifiesthat the implicit geometry partition is enabled for the sequence orslice. The gps_implicit_geom_partition_flag field equal to 0 specifiesthat the implicit geometry partition is disabled for the sequence orslice. When the gps_implicit_geom_partition_flag field is equal to 1,the following two fields, that is, gps_max_num_implicit_qtbt_before_otand gps_min_size_implicit_qtbt are signaled.

The gps_max_num_implicit_qtbt_before_ot field specifies the maximalnumber of implicit QT and BT partitions before OT partitions. Thevariable K is then initialized by thegps_max_num_implicit_qtbt_before_ot field as follows:

K=gps_max_num_implicit_qtbt_before_ot.

The gps_min_size_implicit_qtbt field specifies the minimal size ofimplicit QT and BT partitions. The variable M is then initialized by thegps_min_size_implicit_qtbt field as follows:

M=gps_min_size_implicit_qtbt.

The gps_extension_flag field specifies whether the gps_extension_datasyntax structure is present in the GPS syntax structure. For example,the gps_extension_flag field equal to 1 specifies that thegps_extension_data syntax structure is present in the GPS syntax. Forexample, the gps_extension_flag field equal to 0 specifies that thissyntax structure is not present in the GPS syntax.

When the value of the gps_extension_flag field is equal to 1, the GPSaccording to the embodiments may further include agps_extension_data_flag field.

The gps_extension_data_flag field may have any value. Its presence andvalue do not affect the decoder conformance to profiles.

According to embodiments, the GPS may further include a fieldgeom_tree_type. For example, geom_tree_type equal to 0 indicates thatthe position information (or geometry) is coded using an octree.geom_tree_type equal to 1 indicates that the position information (orgeometry) is coded using a predictive tree.

FIG. 31 shows an embodiment of a syntax structure of a GPS(geometry_parameter_set( )) including slice related information and/orbuffer control related information according to embodiments.

According to embodiments, the GPS may include a fieldgeom_slice_segmentation_enabled_flag.

For example, geom_slice_segmentation_enabled_flag equal to 1 mayindicate that the geometry bitstream is divided into multiple slices andtransmitted. In this case, it may be informed through additionalconditions that parallel processing, scalable transmission, and spatialscalability are possible. Also, geom_slice_segmentation_enabled_flagequal to 1 may indicate that the geometry bitstream is transmitted ineach single slice.

According to embodiments, the slice related information and/or thebuffer control related information of FIG. 31 may be included at anyposition in the GPS of FIG. 30 .

FIG. 32 shows an embodiment of a syntax structure of the attributeparameter set (APS) (attribute_parameter_set( )) according to thepresent disclosure. The APS according to the embodiments may containinformation on a method of encoding attribute information about pointcloud data contained in one or more slices.

The APS according to the embodiments may include anaps_attr_parameter_set_id field, an aps_seq_parameter_set_id field, anattr_coding_type field, an aps_attr_initial_qp field, anaps_attr_chroma_qp_offset field, an aps_slice_qp_delta_present_flagfield, and an aps_extension_flag field.

The aps_attr_parameter_set_id field provides an identifier for the APSfor reference by other syntax elements.

The aps_seq_parameter_set_id field specifies the value ofsps_seq_parameter_set_id for the active SPS.

The attr_coding_type field indicates the coding type for the attribute.

According to embodiments, when the value of the attr_coding_type fieldis 0, it may indicate the coding type is predicting weight lifting. Whenthe value of the attr_coding_type field is 1, it may indicate that thecoding type is RAHT. When the value of the attr_coding_type field is 2,it may indicate that the coding type is fix weight lifting.

The aps_attr_initial_qp field specifies the initial value of thevariable SliceQp for each slice referring to the APS.

The aps_attr_chroma_qp_offset field specifies the offsets to the initialquantization parameter signaled by the syntax aps_attr_initial_qp.

The aps_slice_qp_delta_present_flag field specifies whether theash_attr_qp_delta_luma and ash_attr_qp_delta_chroma syntax elements arepresent in the attribute slice header (ASH). For example, theaps_slice_qp_delta_present_flag field equal to 1 specifies that theash_attr_qp_delta_luma and ash_attr_qp_delta_chroma syntax elements arepresent in the ASH. For example, the aps_slice_qp_delta_present_flagfield specifies that the ash_attr_qp_delta_luma andash_attr_qp_delta_chroma syntax elements are not present in the ASH.

When the value of the attr_coding_type field is 0 or 2, that is, thecoding type is predicting weight lifting or fix weight lifting, the APSaccording to the embodiments may further include alifting_num_pred_nearest_neighbours_minus1 field, alifting_search_range_minus1 field, and a lifting_neighbour_bias[k]field.

The lifting_num_pred_nearest_neighbours_minus1 field plus 1 specifiesthe maximum number of nearest neighbors to be used for prediction.According to embodiments, a value of NumPredNearedtNeighbours is setequal to a value of the lifting_num_pred_nearest_neighbours_minus1field.

The lifting_search_range_minus1 field plus 1 specifies the search rangeused to determine nearest neighbors to be used for prediction and tobuild distance-based levels of detail. The variable LiftingSearchRangefor specifying a search range may acquire by adding 1 to a value of thelifting_search_range_minus1 field(LiftingSearchRange=lifting_search_range_minus1+1).

The lifting_neighbour_bias[k] field specifies a bias used to weight thek-th components in the calculation of the Euclidean distance between twopoints as part of the nearest neighbor derivation process.

According to embodiments, when the value of the attr_coding_type fieldis 2, that is, when the coding type indicates fix weight lifting, theAPS may further include a lifting_scalability_enabled_flag field.

The lifting_scalability_enabled_flag field specifies whether theattribute decoding process allows the pruned octree decode result forthe input geometry points. For example, thelifting_scalability_enabled_flag field equal to 1 specifies that theattribute decoding process allows the pruned octree decode result forthe input geometry points. The lifting_scalability_enabled_flag fieldequal to 0 specifies that that the attribute decoding process requires acomplete octree decode result for the input geometry points.

When the value of the lifting_scalability_enabled_flag field is false,the APS according to the embodiments may further include alifting_num_detail_levels_minus1 field.

The lifting_num_detail_levels_minus1 field plus 1 specifies the numberof levels of detail for the attribute coding. The variableLevelDetailCount for specifying the number of LODs may acquire by adding1 to a value of the lifting_num_detail_levels_minus1 field(LevelDetailCount=lifting_num_detail_levels_minus1+1).

According to embodiments, when the value of thelifting_num_detail_levels_minus1 field is greater than 1, the APS mayfurther include a lifting_lod_regular_sampling_enabled_flag field.

The lifting_lod_regular_sampling_enabled_flag field specifies whetherlevels of detail (LOD) are built by a regular sampling strategy. Forexample, the lifting_lod_regular_sampling_enabled_flag field equal to 1specifies that levels of detail (LOD) are built by using a regularsampling strategy. The lifting_lod_regular_sampling_enabled_flag filedequal to 0 specifies that a distance-based sampling strategy is usedinstead.

When the value of the lifting_scalability_enabled_flag field is false,the APS according to embodiments may include an iteration statementrepeated as many times as the value of thelifting_num_detail_levels_minus1 field. In an embodiment, the index(idx) is initialized to 0 and incremented by 1 every time the iterationstatement is executed, and the iteration statement is repeated until theindex (idx) is greater than the value of thelifting_num_detail_levels_minus1 field. This iteration statement mayinclude a lifting_sampling_period_minus2 [idx] field when the value ofthe lifting_lod_regular_sampling_enabled_flag field is true (e.g., 1),and may include a lifting_sampling_distance_squared_scale_minus1 [idx]field when the value of the lifting_lod_regular_sampling_enabled_flagfield is false (e.g., 0). Furthermore, when the value of the idx is not0 (i.e., idx !=0), the APS may further include alifting_sampling_distance_squared_offset [idx] field.

The lifting_sampling_period_minus2 [idx] field plus 2 specifies thesampling period for the level of detail idx.

The lifting_sampling_distance_squared_scale_minus1 [idx] field plus 1specifies a scale factor for the derivation of the square of thesampling distance for the LOD idx.

The lifting_sampling_distance_squared_offset [idx] field specifies anoffset for the derivation of the square of the sampling distance for theLOD idx.

When the value of the attr_coding_type field is 0, that is, when thecoding type is predicting weight lifting, the APS according to theembodiments may further include a lifting_adaptive_prediction_thresholdfield, a lifting_intra_lod_prediction_num_layers field, alifting_max_num_direct_predictors field, and aninter_component_prediction_enabled_flag field.

The lifting_adaptive_prediction_threshold field specifies the thresholdto enable adaptive prediction. According to embodiments, the variableAdaptivePredictionThreshold specifying a threshold to switch an adaptivepredictor selection mode is set equal to a value of thelifting_adaptive_prediction_threshold field(AdaptivePredictionThreshold=lifting_adaptive_prediction_threshold).

The lifting_intra_lod_prediction_num_layers field specifies the numberof LOD layers where decoded points in the same LOD layer could bereferred to generate a prediction value of a target point. For example,the lifting_intra_lod_prediction_num_layers field equal to a value ofthe variable LevelDetailCount indicates that target point could refer todecoded points in the same LOD layer for all LOD layers. For example,the lifting_intra_lod_prediction_num_layers field equal to 0 indicatesthat target point could not refer to decoded points in the same LoDlayer for any LoD layers. The lifting_max_num_direct_predictors fieldspecifies the maximum number of predictors to be used for directprediction. The value of the lifting_max_num_direct_predictors fieldshall be in the range of 0 to LevelDetailCount.

The inter_component_prediction_enabled_flag field specifies whether theprimary component of a multi component attribute is used to predict thereconstructed value of non-primary components. For example, if theinter_component_prediction_enabled_flag field equal to 1 specifies thatthe primary component of a multi component attribute is used to predictthe reconstructed value of non-primary components. Theinter_component_prediction_enabled_flag field equal to 0 specifies thatall attribute components are reconstructed independently.

When the value of the attr_coding_type field is 1, that is, when theattribute coding type is RAHT, the APS according to the embodiments mayfurther include an raht_prediction_enabled_flag field.

The raht_prediction_enabled_flag field specifies whether the transformweight prediction from the neighbor points is enabled in the RAHTdecoding process. For example, the raht_prediction_enabled_flag fieldequal to 1 specifies the transform weight prediction from the neighborpoints is enabled in the RAHT decoding process. Theraht_prediction_enabled_flag field equal to 0 specifies that thetransform weight prediction is disabled in the RAHT decoding process.

According to embodiments, when the value of theraht_prediction_enabled_flag field is TRUE, the APS may further includea raht_prediction_threshold0 field and a raht_prediction_threshold1field.

The raht_prediction_threshold0 field specifies a threshold to end thetransform weight prediction from the neighbour points.

The raht_prediction_threshold1 field specifies a threshold to skip thetransform weight prediction from the neighbour points.

The aps_extension_flag field specifies whether the aps_extension_datasyntax structure is present in the APS syntax structure. For example,the aps_extension_flag field equal to 1 specifies that theaps_extension_data syntax structure is present in the APS syntaxstructure. For example, the aps_extension_flag field equal to 0specifies that this syntax structure is not present in the APS syntaxstructure.

When the value of the aps_extension_flag field is 1, the APS accordingto the embodiments may further include an aps_extension_data_flag field.

The aps_extension_data_flag field may have any value. Its presence andvalue do not affect decoder conformance to profiles.

The APS according to the embodiments may further include informationrelated to LoD-based attribute compression.

FIG. 32 shows an embodiment of a syntax structure of an APS(attribute_parameter_set( )) including slice related information and/orbuffer control related information according to embodiments.

According to embodiments, the APS may a fieldattr_slice_segmentation_enabled_flag.

For example, attr_slice_segmentation_enabled_flag equal to 1 mayindicate that the attribute bitstream is divided into multiple slicesand transmitted. In this case, it may be informed through additionalconditions that parallel processing, scalable transmission, and spatialscalability are possible. Also, attr_slice_segmentation_enabled_flagequal to 1 may indicate that the attribute bitstream is transmitted ineach single slice.

According to embodiments, the segmented (separated) slice relatedinformation of FIG. 33 and/or information related to direct coding maybe included at any position in the APS of FIG. 32 .

FIG. 34 shows an embodiment of a syntax structure ofgeometry_slice_bitstream( ) according to embodiments.

The geometry slice bitstream (geometry_slice_bitstream( )) according tothe embodiments may include a geometry slice header(geometry_slice_header( )) and geometry slice data (geometry_slice_data()). According to embodiments, the geometry slice bitstream may bereferred to as a geometry data unit, the geometry slice header may bereferred to as a geometry data unit header, and the geometry slice datamay be referred to as geometry data unit data.

FIG. 35 shows an embodiment of a syntax structure of the geometry sliceheader (geometry_slice_header( )) according to the present disclosure.

A bitstream transmitted by the transmission device (or a bitstreamreceived by the reception device) according to the embodiments maycontain one or more slices. Each slice may include a geometry slice andan attribute slice. The geometry slice includes a geometry slice header(GSH). The attribute slice includes an attribute slice header (ASH).

The geometry slice header (geometry_slice_header( )) according toembodiments may include a gsh_geometry_parameter_set_id field, agsh_tile_id field, a gsh_slice_id field, a frame_idx field, agsh_num_points field, and a byte_alignment( ) field.

When the value of the gps_box_present_flag field included in the GPS is‘true’ (e.g., 1), and the value of thegps_gsh_box_log2_scale_present_flag field is ‘true’ (e.g., 1), thegeometry slice header (geometry_slice_header( )) according to theembodiments may further include a gsh_box_log2_scale field, agsh_box_origin_x field, a gsh_box_origin_y field, and a gsh_box_origin_zfield.

The gsh_geometry_parameter_set_id field specifies the value of thegps_geom_parameter_set_id of the active GPS.

The gsh_tile_id field specifies the value of the tile id that isreferred to by the GSH.

The gsh_slice_id field specifies the slice header (or id of the slice)for reference by other syntax elements.

The frame_idx field specifies the log2_max_frame_idx+1 least significantbits of a notional frame number counter. Consecutive slices withdiffering values of frame_idx form parts of different output point cloudframes. Consecutive slices with identical values of frame_idx without anintervening frame boundary marker data unit form parts of the sameoutput point cloud frame.

The gsh_num_points field specifies the maximum number of coded pointswithin the corresponded slice. It is a requirement of bitstreamconformance that a value of the gsh_num_points field is greater than orequal to the number of decoded points in the slice.

The gsh_box_log2_scale field specifies the scaling factor of thebounding box origin for the slice.

The gsh_box_origin_x field specifies the x value of the bounding boxorigin scaled by the value of the gsh_box_log2_scale field.

The gsh_box_origin_y field specifies the y value of the bounding boxorigin scaled by the value of the gsh_box_log2_scale field.

The gsh_box_origin_z field specifies the z value of the bounding boxorigin scaled by the value of the gsh_box_log2_scale field.

In this case, the variables slice_origin_x, slice_origin_y, andslice_origin_z may be derived as follows.

If the gps_gsh_box_log2_scale_present_flag field is equal to 0,originScale is set equal to gsh_box_log2_scale.

If the gps_gsh_box_log2_scale_present_flag field is equal to 1,originScale is set equal to gps_gsh_box_log2_scale.

If the gps_box_present_flag field is equal to 0, the values of thevariables slice_origin_x, slice_origin_y, and slice_origin_z areinferred to be 0.

If the gps_box_present_flag field is equal to 1, the following equationswill be applied to the variables slice_origin_x, slice_origin_y, andslice_origin_z.

slice_origin_x=gsh_box_origin_x<<originScale

slice_origin_y=gsh_box_origin_y<<originScale

slice_origin_z=gsh_box_origin_z<<originScale

When the value of the gps_implicit_geom_partition_flag field is ‘true’(i.e., 0), the geometry slice header ((geometry_slice_header( ))) mayfurther include a gsh_log2_max_nodesize_x field, agsh_log2_max_nodesize_y_minus_x field, and agsh_log2_max_nodesize_z_minus_y field. When the value of thegps_implicit_geom_partition_flag field is ‘false’ (i.e., 1), thegeometry slice header may further include a gsh_log2_max_nodesize field.

The gsh_log2_max_nodesize_x field specifies the bounding box size in thex dimension, i.e., MaxNodesizeXLog2 that is used in the decoding processas follows.

MaxNodeSizeXLog2=gsh_log2_max_nodesize_x

MaxNodeSizeX=1<<MaxNodeSizeXLog2

The gsh_log2_max_nodesize_y_minus_x field specifies the bounding boxsize in the y dimension, i.e., MaxNodesizeYLog2 that is used in thedecoding process as follows.

MaxNodeSizeYLog2=gsh_log2_max_nodesize_y_minus_x+MaxNodeSizeXLog2.

MaxNodeSizeY=1<<MaxNodeSizeYLog2.

The gsh_log2_max_nodesize_z_minus_Y field specifies the bounding boxsize in the z dimension, i.e., MaxNodesizeZLog2 that is used in thedecoding process as follows.

MaxNodeSizeZLog2=gsh_log2_max_nodesize_z_minus_y+MaxNodeSizeYLog2

MaxNodeSizeZ=1<<MaxNodeSizeZLog2

When the value of the gps_implicit_geom_partition_flag field is 1, thegsh_log2_max_nodesize field is obtained as follows.

gsh_log2_max_nodesize=max{MaxNodeSizeXLog2, MaxNodeSizeYLog2,MaxNodeSizeZLog2}

The gsh_log2_max_nodesize field specifies the size of the root geometryoctree node when the gps_implicit_geom_partition_flag field is equal to0.

Here, the variables MaxNodeSize and MaxGeometryOctreeDepth are derivedas follows.

MaxNodeSize=1<<gsh_log2_max_nodesize

MaxGeometryOctreeDepth=gsh_log2_max_nodesize-log2_trisoup_node_size

When the value of the geom_scaling_enabled_flag field is ‘true’, thegeometry slice header (geometry_slice_header( )) according to theembodiments may further include a geom_slice_qp_offset field and ageom_octree_qp_offsets_enabled_flag field.

The geom_slice_qp_offset field specifies an offset to the base geometryquantization parameter geom_base_qp.

The geom_octree_qp_offsets_enabled_flag field specifies whether thegeom_octree_qp_ofsets_depth field is present in the geometry sliceheader. For example, the geom_octree_qp_offsets_enabled_flag field equalto 1 specifies that the geom_octree_qp_offsets_depth field is present inthe geometry slice header. The geom_octree_qp_offsets_enabled_flag fieldequal to 0 specifies that the geom_octree_qp_offsets_depth field is notpresent.

The geom_octree_qp_offsets_depth field specifies the depth of thegeometry octree.

FIG. 36 shows an embodiment of a syntax structure of a geometry dataunit header (or referred to as a geometry slice header) including slicerelated information and/or buffer control related information accordingto embodiments.

The geometry data unit header according to the embodiments may include afield slice_id and a field dependent_neighbour_enabled_flag.

slice_id specifies an identifier for identifying a data unit (i.e., aslice). That is, slice_id may specify an indicator for distinguishing aslice or a data unit, and carry the indicator for a data unit (or calleda slice) belonging to a slice layer. Alternatively, slice_id mayidentify the corresponding slice header for reference by other syntaxelements.

For example, dependent_neighbour_enabled_flag equal to 1 may indicatethat neighbor information outside the slice should be used in the codingoperation. dependent_neighbour_enabled_flag equal to 0 may indicate thatthe neighbor relation is estimated using only the internal informationwithout using the neighbor information outside the slice.

When the value of sps_entropy_continuation_enabled_flag is False (i.e.,0), the geometry data unit header according to the embodiments mayfurther include a field gsh_entropy_continuation_flag. When the value ofsps_entropy_continuation_enabled_flag is True (i.e., 1), the geometrydata unit header may further include a field gsh_prev_slice_id.

The field sps_entropy_continuation_enabled_flag is included in the SPS.When the value of this field is 0, it specifies that the initial entropycontext state of each slice is independent.

For example, gsh_entropy_continuation_flag equal to 1 may indicate thatthe parsing state used in the entropy coding of the current geometrydata unit is dependent upon the final parsing state of the previousgeometry data unit. Also, gsh_entropy_continuation_flag equal to 1 mayindicate that the parsing state used in the entropy coding of theattribute data unit that refers to the current geometry data unit isdependent upon the final parsing state of the previous attribute dataunit.

For example, gsh_entropy_continuation_flag equal to 0 may indicate thatthe parsing state used in the entropy coding of the current geometrydata unit and attribute data unit that refers to the current geometrydata unit do not depend upon any previous data unit. According toembodiments, it is a requirement of bitstream conformance thatgsh_entropy_continuation_flag is equal to 0 when the current geometrydata unit is the first data unit in a point cloud frame.

gsh_prev_slice_id specifies the value of gsh_slice_id (or slice id) ofthe preceding(or previous) geometry data unit in bitstream order.

When geom_slice_segmentation_enabled_flag is equal to 1, the geometrydata unit header may further include a field context_reuse_flag. Also,when context_reuse_flag is equal to 1, the geometry data unit header mayfurther include a field num_context_reuse_minus1.

geom_slice_segmentation_enabled_flag equal to 1 indicates that thegeometry bitstream is divided into multiple slices and transmitted.

For example, context_reuse_flag field equal to 1 may indicate that thecontext of the current slice is used in at least one subsequent slice.According to embodiments, when the reception device uses the contextbuffer control, the context of the current slice may be stored in thecontext buffer for at least one subsequent slice. context_reuse_flagequal to 0 may indicate that the context of the current slice is notused for the subsequent slices.

num_context_reuse_minus1 plus 1 may indicate the number of times thecontext of the current slice is used for subsequent slices.

For example, when the reception device uses the context buffer control,the context of the current slice may be referenced as many times as thenum_context_reuse_minus1+1 through a counter (referred to as a contextreference counter) and then deleted from the context buffer.

The geometry data unit header according to the embodiments includes aniteration statement that is repeated as many times as the value ofnum_context_reuse_minus1. In an embodiment, i is initialized to 0, andis incremented by 1 each time the iteration statement is executed. Theiteration statement is repeated until the value of i becomes equal tothe value of num_context_reuse_minus1. The iteration statement mayinclude a field subsequent_slice_id.

The field subsequent_slice_id may specify an identifier for identifyingthe i-th subsequent slice that uses the current context. That is, thefield subsequent_slice_id may be used to specify a subsequent sliceusing the context of the current slice.

For example, when the reception device uses the context buffer controland a slice (i.e., a subsequent slice) specified throughsubsequent_slice_id is provided, the counter (or referred to as acontext reference counter) may be decremented as shown below or thecurrent context may be referenced as many times asnum_context_reuse_minus1+1 through the counter and then deleted from thecontext buffer. That is, each time the current context is used in asubsequent slice, the counter is decremented by 1. Then, when thecounter reaches 0, the context is deleted from the context buffer.

-   -   NumContextReuse=num_context_reuse_minus1+1    -   If(subsequent_slice_id==slice id)    -   NumContextReuse=NumContextReuse−1

The geometry data unit header according to embodiments may furtherinclude a field num_neighbour_slice whendependent_neighbour_enabled_flag field is equal to 1, and may furtherinclude a field neighbor_occupancy_type whendependent_neighbour_enabled_flag is equal to 0.

The field num_neighbor_slice may indicate the number of slices includingthe corresponding node when referring to node information outside theslice.

The field neighbor_occupancy_type may define an assumption that is madefor a corresponding node when no node information outside the slice isreferred to. For example, neighbor_occupancy_type equal to 0 mayindicate that there is no corresponding neighbor node.neighbor_occupancy_type equal to 1 may indicate that all neighbor nodesare occupied. neighbor_occupancy_type equal to 2 may indicate that theneighbor nodes are non-occupied nodes. neighbor_occupancy_type equal to3 may indicate that occupancy information about nodes in a slicesymmetrical with respect to a central node is used.

The geometry data unit header according to the embodiments includes aniteration statement that is repeated as many times as the value ofnum_neighbor_slice. In an embodiment, i is initialized to 0, and isincremented by 1 each time the iteration statement is executed. Theiteration statement is repeated until the value of i becomes equal tothe value of num_neighbor_slice field. The iteration statement mayinclude a field neighbor slice_id.

The field neighbor_slice_id may specify an identifier for identifyingthe i-th slice including the corresponding node when referring to nodeinformation outside the slice.

According to embodiments, the slice related information and/or thebuffer control related information of FIG. 36 may be included at anyposition in the geometry slice header (i.e., the geometry data unitheader) of FIG. 35 .

FIG. 37 shows an embodiment of a syntax structure of geometry slice data(geometry_slice_data( )) according to the present disclosure. Thegeometry slice data (geometry_slice_data( )) according to theembodiments may carry a geometry bitstream belonging to a correspondingslice (or data unit).

The geometry_slice_data( ) according to the embodiments may include afirst iteration statement repeated as many times as by the value ofMaxGeometryOctreeDepth. In an embodiment, the depth is initialized to 0and is incremented by 1 each time the iteration statement is executed,and the first iteration statement is repeated until the depth becomesequal to MaxGeometryOctreeDepth. The first iteration statement mayinclude a second loop statement repeated as many times as the value ofNumNodesAtDepth. In an embodiment, nodeidx is initialized to 0 and isincremented by 1 each time the iteration statement is executed. Thesecond iteration statement is repeated until nodeidx becomes equal toNumNodesAtDepth. The second iteration statement may includexN=NodeX[depth][nodeIdx], yN=NodeY[depth][nodeIdx],zN=NodeZ[depth][nodeIdx], and geometry_node(depth, nodeIdx, xN, yN, zN).MaxGeometryOctreeDepth indicates the maximum value of the geometryoctree depth, and NumNodesAtDepth[depth] indicates the number of nodesto be decoded at the corresponding depth. The variablesNodeX[depth][nodeIdx], NodeY[depth][nodeIdx], and NodeZ[depth][nodeIdx]indicate the x, y, z coordinates of the Idx-th node in decoding order ata given depth. The geometry bitstream of the node of the depth istransmitted through geometry_node(depth, nodeIdx, xN, yN, zN).

The geometry slice data (geometry_slice_data( )) according to theembodiments may further include geometry_trisoup_data( ) when the valueof the log2_trisoup_node_size field is greater than 0. That is, when thesize of the triangle nodes is greater than 0, a geometry bitstreamsubjected to trisoup geometry encoding is transmitted throughgeometry_trisoup_data( ).

FIG. 38 shows an embodiment of a syntax structure ofattribute_slice_bitstream( ) according to the present disclosure.According to embodiments, the attribute slice bitstream is referred toas an attribute data unit, the attribute slice header is referred to asan attribute data unit header, and the attribute slice data is referredto as an attribute data unit data.

The attribute slice bitstream (attribute_slice_bitstream ( )) accordingto the embodiments may include an attribute slice header(attribute_slice_header( )) and attribute slice data(attribute_slice_data( )).

FIG. 39 shows an embodiment of a syntax structure of an attribute sliceheader (attribute_slice_header( )) according to the present disclosure.

The attribute slice header (attribute_slice_header( )) according to theembodiments may include an ash_attr_parameter_set_id field, anash_attr_sps_attr_idx field, an ash_attr_geom_slice_id field, anash_attr_layer_qp_delta_present_flag field, and anash_attr_region_qp_delta_present_flag field.

When the value of the aps_slice_qp_delta_present_flag field of the APSis ‘true’ (e.g., 1), the attribute_slice_header( ) may further includean ash_attr_qp_delta_luma field and when the value of theattribute_dimension_minus1 [ash_attr_sps_attr_idx] field is greater than0, the attribute_slice_header( ) may further include anash_attr_qp_delta_chroma field.

The ash_attr_parameter_set_id field specifies the value of theaps_attr_parameter_set_id field of the current active APS.

The ash_attr_sps_attr_idx field specifies an attribute set in thecurrently active SPS.

The ash_attr_geom_slice_id field specifies the value of the gsh_slice_idfield of the current geometry slice header.

The ash_attr_qp_delta_luma field specifies a luma delta quantizationparameter (qp) derived from the initial slice qp in the active attributeparameter set.

The ash_attr_qp_delta_chroma field specifies the chroma delta qp derivedfrom the initial slice qp in the active attribute parameter set.

The variables InitialSliceQpY and InitialSliceQpC are derived asfollows.

InitialSliceQpY=aps_attrattr_initial_qp+ash_attr_qp_delta_luma

InitialSliceQpC=aps_attrattr_initial_qp+aps_attr_chroma_qp_offset+ash_attr_qp_delta_chroma

The ash_attr_layer_qp_delta_present_flag field indicates whether theash_attr_layer_qp_delta_luma field and theash_attr_layer_qp_delta_chroma field are present in the attribute sliceheader (ASH) for each layer. For example, theash_attr_layer_qp_delta_present_flag field equal to 1 indicates that theash_attr_layer_qp_delta_luma field and theash_attr_layer_qp_delta_chroma field are present in the ASH. Theash_attr_layer_qp_delta_present_flag field equal to 0 indicates that theash_attr_layer_qp_delta_luma field and theash_attr_layer_qp_delta_chroma field are absent from the ASH.

When the value of the ash_attr_layer_qp_delta_present_flag field isTRUE, the attribute slice header may further include anash_attr_num_layer_qp_minus1 field.

The ash_attr_num_layer_qp_minus1 plus 1 field indicates the number oflayers in which the ash_attr_qp_delta_luma field and theash_attr_qp_delta_chroma field are signaled. When theash_attr_num_layer_qp field is not signaled, the value of theash_attr_num_layer_qp field will be 0. According to embodiments,NumLayerQp, which specifies the number of layers, may be obtainedacquired by adding 0 to the value of the ash_attr_num_layer_qp_minus1field (NumLayerQp=ash_attr_num_layer_qp_minus1+1).

According to embodiments, when the value of theash_attr_layer_qp_delta_present_flag field is TRUE, the geometry sliceheader may include an iteration statement according to the value ofNumLayerQp. In this case, according to an embodiment, i is initializedto 0, and is incremented by 1 each time the iteration statement isexecuted. The iteration statement is iterated until the value of ibecomes equal to the value of NumLayerQp. This iteration statementincludes an ash_attr_layer_qp_delta_luma[i] field. In addition, when thevalue of the attribute_dimension_minus1[ash_attr_sps_attr_idx] field isgreater than 0, the iteration statement may further include anash_attr_layer_qp_delta_chroma[i] field.

The ash_attr_layer_qp_delta_luma field indicates the luma deltaquantization parameter (qp) from the InitialSliceQpY in each layer.

The ash_attr_layer_qp_delta_chroma field indicates the chroma delta qpfrom the InitialSliceQpC in each layer.

The variables SliceQpY[i] and SliceQpC[i] with i=0, . . . ,NumLayerQPNumQPLayer-1 are derived as follows.

for (i=0; i<NumLayerQPNumQPLayer; i++) {

SliceQpY[i]=InitialSliceQpY+ash_attr_layer_qp_delta_luma[i]

SliceQpC[i]=InitialSliceQpC+ash_attr_layer_qp_delta_chroma[i]

}

When the value of the ash_attr_region_qp_delta_present_flag field isequal to 1, the attribute slice header (attribute_slice_header( ))according to the embodiments indicates that ash_attr_region_qp_delta,region bounding box origin, and size are present in the currentattribute slice header. The ash_attr_region_qp_delta_present_flag fieldequal to 0 indicates the ash_attr_region_qp_delta, region bounding boxorigin and size are not present in the current ASH.

In other words, when the ash_attr_layer_qp_delta_present_flag field isequal to 1, the attribute slice header may further include anash_attr_qp_region_box_origin_x field, anash_attr_qp_region_box_origin_y field, anash_attr_qp_region_box_origin_z field, an ash_attr_qp_region_box_widthfield, an ash_attr_qp_region_box_height field, anash_attr_qp_region_box_depth field, and an ash_attr_region_qp_deltafield.

The ash_attr_qp_region_box_origin_x field indicates the x offset of theregion bounding box relative to slice_origin_x.

The ash_attr_qp_region_box_origin_y field indicates the y offset of theregion bounding box relative to slice_origin_y.

The ash_attr_qp_region_box_origin_z field i indicates the z offset ofthe region bounding box relative to slice_origin_z.

The ash_attr_qp_region_box_size_width field indicates the width of theregion bounding box.

The ash_attr_qp_region_box_size_height field indicates the height of theregion bounding box.

The ash_attr_qp_region_box_size_depth field indicates the depth of theregion bounding box.

The ash_attr_region_qp_delta field specifies the delta qp from theSliceQpY[i] and SliceQpC[i] of the region specified.

According to embodiments, the variable RegionboxDeltaQp specifying theregion box delta quantization parameter is set equal to the value of theash_attr_region_qp_delta field(RegionboxDeltaQp=ash_attr_region_qp_delta).

FIG. 40 shows an embodiment of a syntax structure of an attribute dataunit header (or referred to as an attribute slice header) includingslice related information and/or buffer control related informationaccording to embodiments.

The attribute data unit header may include a field slice_id and a fielddependent_neighbor_enabled_flag.

The slice_id field indicates an identifier for identifying acorresponding data unit (i.e., a slice). That is, the slice_id fieldindicates an indicator for distinguishing a slice or a data unit, andmay deliver an indicator for a data unit (or called a slice) belongingto a slice layer. Alternatively, the slice_id field may identify acorresponding slice header for reference by other syntax elements.

For example, dependent_neighbour_enabled_flag equal to 1 may indicatethat neighbor information outside the slice should be used in the codingoperation. dependent_neighbour_enabled_flag equal to 0 may indicate thatthe neighbor relation is estimated using only the internal informationwithout using the neighbor information outside the slice.

When the value of sps_entropy_continuation_enabled_flag is False (i.e.,0), the attribute data unit header according to the embodiments mayfurther include a field ash_entropy_continuation_flag. When the value ofsps_entropy_continuation_enabled_flag is True (i.e., 1), the attributedata unit header may further include a field ash_prev_slice_id.

The field sps_entropy_continuation_enabled_flag is included in the SPS.When the value of this field is 0, it specifies that the initial entropycontext state of each slice is independent.

For example, ash_entropy_continuation_flag equal to 1 may indicate thatthe parsing state used in the entropy coding of the current attributedata unit is dependent upon the final parsing state of the previousattribute data unit. ash_entropy_continuation_flag equal to 0 mayindicate that the parsing state used in the entropy coding of thecurrent attribute data unit does not depend upon any previous data unit.According to embodiments, it is a requirement of bitstream conformancethat ash_entropy_continuation_flag is equal to 0 when the currentattribute data unit is the first data unit in a point cloud frame.

ash_prev_slice_id specifies the value of ash_slice_id (or slice id) ofthe preceding attribute data unit in bitstream order.

When attr_slice_segmentation_enabled_flag is equal to 1, the attributedata unit header may further include a field context_reuse_flag. Also,when context_reuse_flag is equal to 1, the attribute data unit headermay further include a field num_context_reuse_minus1.

attr_slice_segmentation_enabled_flag equal to 1 indicates that theattribute bitstream is divided into multiple slices and transmitted.

For example, context_reuse_flag field equal to 1 may indicate that thecontext of the current slice is used in at least one subsequent slice.According to embodiments, when the reception device uses the contextbuffer control, the context of the current slice may be stored in thecontext buffer for at least one subsequent slice. context_reuse_flagequal to 0 may indicate that the context of the current slice is notused for the subsequent slices.

num_context_reuse_minus1 plus 1 may indicate the number of times thecontext of the current slice is used for subsequent slices.

For example, when the reception device uses the context buffer control,the context of the current slice may be referenced as many times as thenum_context_reuse_minus1+1 through a counter (referred to as a contextreference counter) and then deleted from the context buffer.

The attribute data unit header according to the embodiments includes aniteration statement that is repeated as many times as the value ofnum_context_reuse_minus1. In an embodiment, i is initialized to 0, andis incremented by 1 each time the iteration statement is executed. Theiteration statement is repeated until the value of i becomes equal tothe value of num_context_reuse_minus1. The iteration statement mayinclude a field subsequent_slice_id.

The field subsequent_slice_id may specify an identifier for identifyingthe i-th subsequent slice that uses the current context. That is, thefield subsequent_slice_id may be used to specify a subsequent sliceusing the context of the current slice.

For example, when the reception device uses the context buffer controland a slice (i.e., a subsequent slice) specified throughsubsequent_slice_id is provided, the counter (or referred to as acontext reference counter) may be decremented as shown below or thecurrent context may be referenced as many times asnum_context_reuse_minus1+1 through the counter and then deleted from thecontext buffer.

-   -   NumContextReuse=num_context_reuse_minus1+1    -   If(subsequent_slice_id==slice id)    -   NumContextReuse=NumContextReuse−1

The attribute data unit header according to embodiments may furtherinclude a field num_neighbour_slice whendependent_neighbour_enabled_flag field is equal to 1, and may furtherinclude a field neighbor_occupancy_type whendependent_neighbour_enabled_flag is equal to 0.

The field num_neighbor_slice may indicate the number of slices includingthe corresponding node when referring to node information outside theslice.

The field neighbor_occupancy_type may define an assumption that is madefor a corresponding node when no node information outside the slice isreferred to. For example, neighbor_occupancy_type equal to 0 mayindicate that there is no corresponding neighbor node.neighbor_occupancy_type equal to 1 may indicate that all neighbor nodesare occupied. neighbor_occupancy_type equal to 2 may indicate that theneighbor nodes are non-occupied nodes. neighbor_occupancy_type equal to3 may indicate that occupancy information about nodes in a slicesymmetrical with respect to a central node is used.

The attribute data unit header according to the embodiments includes aniteration statement that is repeated as many times as the value ofnum_neighbor_slice. In an embodiment, i is initialized to 0, and isincremented by 1 each time the iteration statement is executed. Theiteration statement is repeated until the value of i becomes equal tothe value of num_neighbor_slice field. The iteration statement mayinclude a field neighbor slice_id.

The field neighbor_slice_id may specify an identifier for identifyingthe i-th slice including the corresponding node when referring to nodeinformation outside the slice.

According to embodiments, the slice related information and/or thebuffer control related information of FIG. 40 may be included at anyposition in the attribute slice header (i.e., the attribute data unitheader) of FIG. 39 .

FIG. 41 shows a syntax structure of attribute slice data(attribute_slice_data( )) according to an embodiment of the presentdisclosure. The attribute slice data (attribute_slice_data( )) may carryan attribute bitstream belonging to a corresponding slice. The attributeslice data may include an attribute or attribute related data inrelation to a part or the entirety of the point cloud.

In attribute_slice_data( ) in FIG. 41 ,dimension=attribute_dimension[ash_attr_sps_attr_idx] representsattribute_dimension of an attribute set identified byash_attr_sps_attr_idx in the attribute slice header. attribute_dimensionindicates the number of components constituting an attribute. Theattribute according to the embodiments represents reflectance, color, orthe like. Accordingly, the number of components differs amongattributes. For example, an attribute corresponding to the color mayhave three color components (e.g., RGB). Accordingly, an attributecorresponding to the reflectance may be a mono-dimensional attribute,and an attribute corresponding to the color may be a three-dimensionalattribute.

The attributes according to the embodiments may be attribute-encoded ona per dimension basis.

For example, the attribute corresponding to the reflectance and theattribute corresponding to the color may be attribute-encoded,respectively. The attributes according to embodiments may beattribute-encoded regardless of dimensions. For example, the attributecorresponding to the reflectance and the attribute corresponding to thecolor may be attribute-encoded together.

In FIG. 41 , zerorun specifies the number of 0 prior to residual.

In FIG. 41 , i denotes an i-th point value of the attribute. Accordingto an embodiment, the fields attr_coding_type andlifting_adaptive_prediction_threshold are signaled in the APS.

MaxNumPredictors of FIG. 41 is a variable used in the point cloud datadecoding operation, and may be acquired based on the value oflifting_adaptive_prediction_threshold field signaled in the APS asfollows.

MaxNumPredictors=lifting_max_num_direct_predicots+1

Here, lifting_max_num_direct_predictors indicates the maximum number ofpredictors to be used for direct prediction.

According to the embodiments, predIindex[i] specifies the predictorindex (or prediction mode) to decode the i-th point value of theattribute. The value of predIndex[i] is in the range from 0 to the valueof lifting_max_num_direct_predictors.

FIG. 42 shows a structure of a point cloud data transmission deviceaccording to embodiments.

The transmission device of FIG. 42 corresponds to the transmissiondevice 10000 of FIG. 1 , the point cloud video encoder 10002 of FIG. 1 ,the transmitter 10003 of FIG. 1 , the acquisition 20000/encoding20001/transmission 20002 of FIG. 2 , the encoder of FIG. 4 , thetransmission device of FIG. 12 , the device of FIG. 14 , the encoder ofFIG. 20 , and the like. Each component of FIG. 42 may correspond tohardware, software, a processor, and/or a combination thereof.

The encoder and the transmitter according to the embodiments operate asdescribed below.

When point cloud data is input to the transmission device, a geometryencoder 60010 encodes position information (geometry data (e.g., XYZcoordinates, phi-theta coordinates, etc.)) in the point cloud data, andan attribute encoder 60020 encodes attribute data (e.g., color,reflectance, intensity, grayscale, opacity, medium, material,glossiness, etc.) in the point cloud data.

The compressed (encoded) data is divided into units for transmission.The data may be divided by a sub-bitstream generator 60040 into unitssuitable to select necessary information in the bitstream unit accordingto layering structure information and may then be packed.

According to embodiments, the geometry bitstream output from thegeometry encoder 60010 and/or the attribute bitstream output from theattribute encoder 60020 are input to the sub-bitstream generator 60040.The sub-bitstream generator 60040 configures multiple slices bysegmenting each bitstream into multiple sub-bitstreams based on theslice related information and/or buffer control related informationoutput from the metadata generator 60030. For details of thesegmentation of each bitstream and the configuration of slices,reference will be made to FIGS. 17 to 24 described above, anddescriptions of the details will be omitted. According to embodiments,the slice related information includes layering structure information.The slice related information indicates the configuration, sorting, andselection of a bitstream, and slice configuration described withreference to FIGS. 17 to 24 , and represents the information shown inFIGS. 27 to 41 and the like.

According to embodiments, slice related information including layeringstructure information, and/or buffer control related information may begenerated by the metadata generator 60030.

The slice related information and/or buffer control related informationmay be included in at least one of the SPS, GPS, TPS, APS, geometryslice header, attribute slice header, and SEI message to be transmittedto the reception device. The slice related information and/or buffercontrol related information may include one or more of the fieldssps_entropy_continuation_enabled_flag,geom_slice_segmentation_enabled_flag,attr_slice_segmentation_enabled_flag, slice id,gsh_entropy_continuation_flag, gsh_prev_slice_id, context_reuse_flag,num_context_reuse_minus1, subsequent slice_id,dependent_neighbour_enabled_flag, num_neighbour_slice,neighbour_slice_id, neighbour_occupancy_type, ash_continuation_flag,ash_prev_slice_id. For details of each field mentioned above, referencewill be made to the description of FIGS. 27 to 41 , and detaileddescription of the fields will be omitted.

In another embodiment, the sub-bitstream generator 60040 may segmenteach bitstream, generate slice related information (or layeringstructure information) indicating segmentation processing, and transmitthe slice related information to the metadata generator 60030. Themetadata generator 60030 may receive information indicating geometryencoding processing and attribute encoding processing from the encoders60010 and 60020, and generate metadata (parameters).

According to embodiments, the sub-bitstream generator 60040 performs aslice segmentation operation based on the slice related informationand/or buffer related information provided by the metadata generator60030 in order to transmit multiple sub-bitstreams segmented from ageometry bitstream through multiple slices. In addition, thesub-bitstream generator 60040 performs the slice segmentation operationbased on the slice related information and/or buffer related informationprovided by the metadata generator 60030 in order to transmit multiplesub-bitstreams segmented from an attribute bitstream through multipleslices. That is, each of the geometry bitstream (or geometry data) andthe attribute bitstream (or attribute data) may be transmitted throughmultiple slices. Accordingly, the reception device may perform selectivedecoding or parallel decoding.

According to embodiments, multiple slices containing the geometry datamay be transmitted first, and then multiple slices containing theattribute data may be transmitted. For details, reference will be madeto the description of FIG. 23 and description of the details will beomitted herein.

According to other embodiments, slices of the geometry data and slicesof the attribute data may be transmitted according to layers. Fordetails, reference will be made to the description of FIG. 24 anddescription of the details will be omitted herein.

According to embodiments, the multiple slices may be independent of eachother or may have a dependency relationship with each other. Accordingto embodiments, for octree-based geometry coding, compressionperformance may be enhanced by sequentially and cumulatively usingcontext information about previous nodes. In addition, in neighborsearch and intra prediction, decoded occupancy information about aneighbor (or peripheral) node is first used. In this case, informationabout the previous slice may be used. Alternatively, the informationabout the preceding slice may be used for parallel processing. In thiscase, dependency between slices occurs. In another embodiment, at leastone slice may be independent without a relation to another slice. Fordetails of the slice having a dependency and/or an independent slice,reference will be made to the description of FIGS. 20 to 25 , anddescription of the details will be omitted herein.

According to embodiments, when data (e.g., geometry data or attributedata) belonging to each slice is encoded by the encoder, a context isgenerated for each slice. In this regard, when the context iscontinuously used, it is necessary to control the context buffer of thereception device. According to embodiments, details about the contextbuffer control have been described with reference to FIGS. 25A to 26D,and thus description thereof will be omitted. Also, signalinginformation (e.g., slice related information and/or buffer controlrelated information) for control of the context buffer of the receptiondevice has been described with reference to FIGS. 27 to 41 , and thusdescription thereof will omitted herein.

The multiplexer 60060 multiplexes the multiple segments output from thesub-bitstream generator 60040 and the signaling information generated bythe metadata generator 60050 and outputs multiplexed data to thetransmitter 60070. Multiplexing of the multiplexer 60050 may beperformed for each layer. For details of the slice related informationand/or buffer control related information generated by the metadatagenerator 60030, refer to FIGS. 27 to 48 .

The transmitter 60060 according to the embodiments transmits the data(or a bitstream in slices) multiplexed by the multiplexer 60050. Thebitstream according to the embodiments may be encapsulated in a file orsegment (e.g., a streaming segment) and transmitted over variousnetworks such as a broadcasting network and/or a broadband network.Although not shown in the figure, the transmitter 60060 may include anencapsulator (or an encapsulation module) configured to perform anencapsulation operation.

FIG. 43 shows a structure of a point cloud reception device according toembodiments.

The reception device according to the embodiments of FIG. 43 correspondsto the reception device 10004, the receiver 10005 of FIG. 1 , the pointcloud video decoder 10006 of FIG. 1 , the transmission 20002/decoding20003/rendering 20004 of FIG. 2 , the decoder of FIG. 10 , the decoderof FIG. 11 , the reception device of FIG. 13 , the device of FIG. 14 ,and the like. Each component of FIG. 43 may correspond to hardware,software, a processor, and/or a combination thereof.

The decoder/receiver according to the embodiments operates as follows.

When a bitstream is input to a receiver 65010 of the reception device,the receiver 65010 outputs a bitstream to a demultiplexer 65020, and thedemultiplexer 65020 divides the bitstream into a bitstream includinggeometry information and attribute information, signaling informationincluding slice related information and/or buffer control relatedinformation.

The bitstream including the divided geometry information and attributeinformation is output to a sub-bitstream classifier 65040, and thedivided signaling information is output to the metadata parser 65030.

The sub-bitstream classifier 65040 processes the bitstream including thegeometry information and the attribute information based on informationin the header of each of the one or more slices, and/or the slicerelated information, and/or the buffer control related information.Then, it outputs the bitstream (or sub-bitstream) including the geometryinformation to a geometry decoder 65060, and outputs the bitstream (orsub-bitstream) including the attribute information to an attributedecoder 65080.

Alternatively, in this process, a layer required by the receiver may beselected. Geometry data and attribute data may be reconstructed from theclassified bitstream according to the characteristics of the data by thegeometry decoder 65060 and the attribute decoder 65080, respectively,and may then be converted into a format for final output by the renderer65090.

According to embodiments, the sub-bitstream classifier mayclassify/select a bitstream based on the metadata (e.g., slice relatedinformation and/or buffer control related information) acquired by themetadata parser 65030.

The slice related information and/or buffer control related informationmay be received through at least one of the SPS, GPS, TPS, APS, geometryslice header, attribute slice header, or SEI message. The slice relatedinformation and/or buffer control related information may include one ormore of the fields sps_entropy_continuation_enabled_flag,geom_slice_segmentation_enabled_flag,attr_slice_segmentation_enabled_flag, slice_id,gsh_entropy_continuation_flag, gsh_prev_slice_id, context_reuse_flag,num_context_reuse_minus1, subsequent slice id,dependent_neighbour_enabled_flag, num_neighbour_slice, neighbourslice_id, neighbour_occupancy_type, ash_continuation_flag, andash_prev_slice_id. For details of each field mentioned above, referencewill be made to the description of FIGS. 27 to 41 , and detaileddescription of the fields will be omitted.

According to embodiments, the point cloud data includes position (i.e.,geometry) information about each point and attribute information such ascolor/brightness/reflectance, which are compressed and transmitted tothe reception device. In this regard, in order to allow the receptiondevice to decode or represent only a part of the point cloud dataaccording to the performance of the reception device or the transmissionspeed, the transmission device may divide the point cloud data (or thecoded bitstream) into multiple slices. Then, multiple slices aresignaled and dependencies between the slices are defined. Thereby, thecurrent slice uses information generated in the previous slice. In thiscase, the buffer of the reception device needs to be controlled.

According to embodiments, the geometry decoder 60060 may control thegeometry buffer 65050 based on the slice related information and/orbuffer control related information provided from the metadata parser65030. According to an embodiment, the geometry buffer 65050 may be thecontext buffer described with reference to FIGS. 25A to 26E. Forexample, when the geometry context of the current slice is used in asubsequent slice, the geometry context of the current slice is stored inthe geometry buffer 65050 and matched. The stored information may beused until the context counter (e.g., N or num_reuse_minus1) becomes 0or when a matching subsequent slice identifier (slice id) is received.Alternatively, when neighbor node information (e.g.,dependent_neighbour_enabled_flag==1) is used as described with referenceto FIGS. 26A to 26D, the node information may be stored in the geometrybuffer 65050 and used when necessary. For details the management (orcontrol) of the geometry buffer 65050, reference will be made to FIGS.25A to 25E and FIG. 41 , and a description of the details will beomitted herein.

According to embodiments, the attribute decoder 60680 may control theattribute buffer 65070 based on the slice related information and/orbuffer control related information provided from the metadata parser65030. According to an embodiment, the attribute buffer 65070 may be thecontext buffer described with reference to FIGS. 25A to 26D. For detailsthe management (or control) of the attribute buffer 65070, referencewill be made to FIGS. 25A to 25E and FIG. 41 , and a description of thedetails will be omitted herein.

As described above, for efficient management of the buffer (or contextbuffer) of the reception device, signaling may be provided to indicatewhether coding information/node information (e.g., slice relatedinformation and/or buffer control related information) about the currentslice is used in a subsequent slice, and storage and deletion of thecontext of the current slice in the buffer may be managed based on theindication. Thereby, the buffer of the receiver may be efficientlymanaged. That is, even when the transmission device divides the pointcloud data into multiple slices and transmits the same, the compressionefficiency may be enhanced by allowing continuous coding informationand/or neighbor node information to be used. In addition, since thereception device is allowed to recognize whether coding information/nodeinformation (e.g., slice related information and/or buffer controlrelated information) about the current slice is used in a subsequentslice, buffer management may be efficiently performed. For example, thereception device may efficiently manage resources by predeterminingwhether the context of the current slice is used in a subsequent slice.

A point cloud data transmission method, a point cloud data transmissiondevice, a point cloud data reception method, and a point cloud datareception device according to embodiments may provide a good-qualitypoint cloud service.

A point cloud data transmission method, a point cloud data transmissiondevice, a point cloud data reception method, and a point cloud datareception device according to embodiments may achieve various videocodec methods.

A point cloud data transmission method, a point cloud data transmissiondevice, a point cloud data reception method, and a point cloud datareception device according to embodiments may provide universal pointcloud content such as an autonomous driving service.

A point cloud data transmission method, a point cloud data transmissiondevice, a point cloud data reception method, and a point cloud datareception device according to embodiments may perform space-adaptivepartition of point cloud data for independent encoding and decoding ofthe point cloud data, thereby improving parallel processing andproviding scalability.

A point cloud data transmission method, a point cloud data transmissiondevice, a point cloud data reception method, and a point cloud datareception device according to embodiments may perform encoding anddecoding by partitioning the point cloud data in units of tiles and/orslices, and signal necessary data therefor, thereby improving encodingand decoding performance of the point cloud.

For the point cloud data, a point cloud data transmission method, apoint cloud data transmission device, a point cloud data receptionmethod, and a point cloud data reception device according to embodimentsmay divide and transmit compressed data according to a predeterminedcriterion. In addition, when layered coding is used, the compressed datamay be divided and transmitted according to layers. Accordingly, thestorage and transmission efficiency of the transmission device may beincreased.

With a point cloud data transmission method, a point cloud datatransmission device, a point cloud data reception method, and a pointcloud data reception device according to embodiments, when a bitstreamis divided and transmitted in slices, the receiver may selectivelydeliver the bitstream to the decoder according to the density of thepoint cloud data to be represented according to decoder performance orapplication field. In this case, since selection is made beforedecoding, decoder efficiency may be increased, and decoders of variousperformances may be supported.

With a point cloud data transmission method, a point cloud datatransmission device, a point cloud data reception method, and a pointcloud data reception device according to embodiments, signaling may beprovided to indicate whether coding information/node information aboutthe current slice is used in a subsequent slice, and storage anddeletion of the context of the current slice in the buffer may bemanaged based on the indication for efficient management of the buffer(or context buffer) of the reception device. Thereby, the buffer of thereceiver may be efficiently managed. That is, even when the transmissiondevice divides the point cloud data into multiple slices and transmitsthe same, the compression efficiency may be enhanced by allowingcontinuous coding information and/or neighbor node information to beused. In addition, since the reception device is allowed to recognizewhether coding information/node information about the current slice isused in a subsequent slice, buffer management may be efficientlyperformed. For example, the receiver may efficiently manage resources bypredetermining whether the context of the current slice is used in asubsequent slice.

Each part, module, or unit described above may be a software, processor,or hardware part that executes successive procedures stored in a memory(or storage unit). Each of the steps described in the above embodimentsmay be performed by a processor, software, or hardware parts. Eachmodule/block/unit described in the above embodiments may operate as aprocessor, software, or hardware. In addition, the methods presented bythe embodiments may be executed as code. This code may be written on aprocessor readable storage medium and thus read by a processor providedby an apparatus.

In the specification, when a part “comprises” or “includes” an element,it means that the part further comprises or includes another elementunless otherwise mentioned. Also, the term “ . . . module(or unit)”disclosed in the specification means a unit for processing at least onefunction or operation, and may be implemented by hardware, software orcombination of hardware and software.

Although embodiments have been explained with reference to each of theaccompanying drawings for simplicity, it is possible to design newembodiments by merging the embodiments illustrated in the accompanyingdrawings. If a recording medium readable by a computer, in whichprograms for executing the embodiments mentioned in the foregoingdescription are recorded, is designed by those skilled in the art, itmay fall within the scope of the appended claims and their equivalents.

The apparatuses and methods may not be limited by the configurations andmethods of the embodiments described above. The embodiments describedabove may be configured by being selectively combined with one anotherentirely or in part to enable various modifications.

Although preferred embodiments have been described with reference to thedrawings, those skilled in the art will appreciate that variousmodifications and variations may be made in the embodiments withoutdeparting from the spirit or scope of the disclosure described in theappended claims. Such modifications are not to be understoodindividually from the technical idea or perspective of the embodiments.

Various elements of the apparatuses of the embodiments may beimplemented by hardware, software, firmware, or a combination thereof.Various elements in the embodiments may be implemented by a single chip,for example, a single hardware circuit. According to embodiments, thecomponents according to the embodiments may be implemented as separatechips, respectively. According to embodiments, at least one or more ofthe components of the apparatus according to the embodiments may includeone or more processors capable of executing one or more programs. Theone or more programs may perform any one or more of theoperations/methods according to the embodiments or include instructionsfor performing the same. Executable instructions for performing themethod/operations of the apparatus according to the embodiments may bestored in a non-transitory CRM or other computer program productsconfigured to be executed by one or more processors, or may be stored ina transitory CRM or other computer program products configured to beexecuted by one or more processors. In addition, the memory according tothe embodiments may be used as a concept covering not only volatilememories (e.g., RAM) but also nonvolatile memories, flash memories, andPROMs. In addition, it may also be implemented in the form of a carrierwave, such as transmission over the Internet. In addition, theprocessor-readable recording medium may be distributed to computersystems connected over a network such that the processor-readable codemay be stored and executed in a distributed fashion.

In this document, the term “/” and “,” should be interpreted asindicating “and/or.” For instance, the expression “A/B” may mean “Aand/or B.” Further, “A, B” may mean “A and/or B.” Further, “A/B/C” maymean “at least one of A, B, and/or C.” “A, B, C” may also mean “at leastone of A, B, and/or C.” Further, in the document, the term “or” shouldbe interpreted as “and/or.” For instance, the expression “A or B” maymean 1) only A, 2) only B, and/or 3) both A and B. In other words, theterm “or” in this document should be interpreted as “additionally oralternatively.”

Various elements of the embodiments may be implemented by hardware,software, firmware, or a combination thereof. Various elements in theembodiments may be implemented by a single chip, for example, a singlehardware circuit. Optionally, the components may be implemented asseparate chips, respectively. According to embodiments, at least one ofthe components according to the embodiments may be implemented in one ormore processors including instructions for performing operationsaccording to embodiments.

In addition, the operations according to the embodiments described inthe present disclosure may be performed by a transmission/receptiondevice including one or more memories and/or one or more processorsaccording to embodiments. The one or more memories may store programsfor processing/controlling operations according to embodiments. The oneor more processors may control various operations described in thepresent disclosure. The one or more processors may be referred to ascontrollers or the like. The operations according to the embodiments maybe performed by firmware, software, and/or a combination thereof. Thefirmware, software, and/or a combination thereof may be stored in aprocessor or a memory.

Terms such as first and second may be used to describe various elementsof the embodiments. However, various components according to theembodiments should not be limited by the above terms. These terms areonly used to distinguish one element from another. For example, a firstuser input signal may be referred to as a second user input signal.Similarly, the second user input signal may be referred to as a firstuser input signal. Use of these terms should be construed as notdeparting from the scope of the various embodiments. The first userinput signal and the second user input signal are both user inputsignals, but do not mean the same user input signal unless contextclearly dictates otherwise.

The terminology used to describe the embodiments is used for the purposeof describing particular embodiments only and is not intended to belimiting of the embodiments. As used in the description of theembodiments and in the claims, the singular forms “a”, “an”, and “the”include plural referents unless the context clearly dictates otherwise.The expression “and/or” is used to include all possible combinations ofterms. The terms such as “includes” or “has” are intended to indicateexistence of figures, numbers, steps, elements, and/or components andshould be understood as not precluding possibility of existence ofadditional existence of figures, numbers, steps, elements, and/orcomponents. As used herein, conditional expressions such as “if” and“when” are not limited to an optional case and are intended to beinterpreted, when a specific condition is satisfied, to perform therelated operation or interpret the related definition according to thespecific condition. Embodiments may include variations/modificationswithin the scope of the claims and their equivalents.

It will be apparent to those skilled in the art that variousmodifications and variations can be made in the present inventionwithout departing from the spirit and scope of the invention. Thus, itis intended that the present invention cover the modifications andvariations of this invention provided they come within the scope of theappended claims and their equivalents.

What is claimed is:
 1. A method of transmitting point cloud data, themethod comprising: encoding geometry data of the point cloud data;encoding attribute data of the point cloud data based on the geometrydata; and transmitting the encoded geometry data, the encoded attributedata, and signaling data, wherein the encoded geometry data is includedin a plurality of slices, wherein the signaling data includes flaginformation for indicating whether or not a context of a current sliceis referenced by at least one other slice and slice identificationinformation for identifying the current slice, and wherein the contextof the current slice is not stored in a buffer of a receiving system forat least one other slice based on the flag information indicating thatthe context of the current slice is not referenced by the at least oneother slice.
 2. The method of claim 1, wherein the context of thecurrent slice is stored in the buffer of the receiving system fordecoding the at least one other slice based on the flag informationindicating that the context of the current slice is referenced by the atleast one other slice.
 3. The method of claim 1, wherein the signalingdata further includes information identifying a number of times thecontext of the current slice is referenced based on the context of thecurrent slice being referenced by the at least one other slice.
 4. Anapparatus for transmitting point cloud data, the apparatus comprising: ageometry encoder configured to encode geometry data of the point clouddata; an attribute encoder configured to encode attribute data of thepoint cloud data based on the geometry data; and a transmitterconfigured to transmit the encoded geometry data, the encoded attributedata, and signaling data, wherein the encoded geometry data is includedin a plurality of slices, wherein the signaling data includes flaginformation for indicating whether or not a context of a current sliceis referenced by at least one other slice and slice identificationinformation for identifying the current slice, and wherein the contextof the current slice is not stored in a buffer of a receiving system forat least one other slice based on the flag information indicating thatthe context of the current slice is not referenced by the at least oneother slice.
 5. The apparatus of claim 4, wherein the context of thecurrent slice is stored in the buffer of the receiving system fordecoding the at least one other slice based on the flag informationindicating that the context of the current slice is referenced by the atleast one other slice.
 6. The apparatus of claim 4, wherein thesignaling data further includes information identifying a number oftimes the context of the current slice is referenced based on thecontext of the current slice being referenced by the at least one otherslice.
 7. A method of receiving point cloud data, the method comprising:receiving geometry data, attribute data, and signaling data; decodingthe geometry data based on the signaling data; decoding the attributedata based on the signaling data and the decoded geometry data; andrendering the point cloud data based on the signaling data, the decodedgeometry data, and the decoded attribute data, wherein the geometry datais included in a plurality of slices, wherein the signaling dataincludes flag information for indicating whether or not a context of acurrent slice is referenced by at least one other slice and sliceidentification information for identifying the current slice, andwherein, based on the flag information indicating that the context ofthe current slice is not referenced by the at least one other slice, thecontext of the current slice is not stored in a buffer for at least oneother slice.
 8. The method of claim 7, wherein the signaling datafurther includes information identifying a number of times the contextof the current slice is referenced based on the context of the currentslice being referenced by the at least one other slice.
 9. The method ofclaim 7, wherein, based on the flag information indicating that thecontext of the current slice is referenced by the at least one otherslice the context of the current slice is stored in the buffer fordecoding the at least one other slice.
 10. An apparatus for receivingpoint cloud data, the apparatus comprising: a receiver configured toreceive geometry data, attribute data, and signaling data; a geometrydecoder configured to decode the geometry data based on the signalingdata; an attribute decoder configured to decode the attribute data basedon the signaling data and the decoded geometry data; and a rendererconfigured to render the point cloud data based on the signaling data,the decoded geometry data, and the decoded attribute data, wherein thegeometry data is included in a plurality of slices, wherein thesignaling data includes flag information for indicating whether or not acontext of a current slice is referenced by at least one other slice andslice identification information for identifying the current slice, andwherein, based on the flag information indicating that the context ofthe current slice is not referenced by the at least one other slice, thecontext of the current slice is not stored in a buffer for at least oneother slice.
 11. The apparatus of claim 10, wherein the signaling datafurther includes information identifying a number of times the contextof the current slice is referenced based on the context of the currentslice being referenced by the at least one other slice.
 12. Theapparatus of claim 10, wherein, based on the flag information indicatingthat the context of the current slice is referenced by the at least oneother slice, the context of the current slice is stored in the bufferfor decoding the at least one other slice.